text:
Dunedin Public Hospital
Dunedin Hospital is the main public hospital in Dunedin, New Zealand. It serves as the major base hospital for the Otago and Southland regions with a potential catchment radius of roughly 300 kilometres, and a population of around 300,000.
Dunedin Hospital
Southern District Health Board
© Benchill, CC BY 3.0
Dunedin Hospital from Signal Hill
Dunedin, New Zealand, Otago, New Zealand
Care system
Publicly funded
Teaching, Tertiary Referral
Affiliated university
University of Otago
400 (per 2015 audit)
ICAO: NZDH
https://www.southernhealth.nz/
Hospitals in New Zealand
1 Operations
1.1 Queen Mary Maternity Centre
1.2 Helipad
2.1 2007 Norovirus outbreak
2.2 Rebuild
Dunedin Hospital is New Zealand's largest hospital south of Christchurch.[1] Patients are transferred or sent to this tertiary level care hospital from smaller secondary care hospitals across Otago and Southland including Dunstan Hospital in Clyde, Lakes District Hospital in Queenstown and Oamaru, Gore and Invercargill hospitals. Dunedin Hospital is the major trauma centre for the Otago region and the tertiary major trauma centre for the Otago and Southland regions.[2]
Dunedin Hospital is operated by the Southern District Health Board, formed by the amalgamation of the Otago District Health Board and Southland District Health Board. It is located in the central business district of Dunedin close to the University of Otago, occupying the city block bounded by Great King Street, Hanover Street, Cumberland Street and Frederick Street. It is an approximately 400-bed tertiary hospital and is affiliated with the University of Otago. It has approximately 3,000 staff members.[3]
Queen Mary Maternity Centre
Dunedin Hospital includes the Queen Mary Maternity Centre. The maternity unit directly replaced the nearby Queen Mary Hospital, which opened in 1937. Queen Mary in turn directly replaced the Batchelor Hospital, originally known as Forth Street Maternity Hospital.[4]
The Otago Regional Rescue Helicopter taking off from the hospital helipad
The Ward Block building has a helipad on the roof of the northeast corner (ICAO: NZDH).[5] The building was designed with consideration for a helipad, and, after substantial fundraising, one was built on the roof in circa 2000. The hospital helipad improves patient care, reducing the need for ambulance transfers between a remote helipad and the hospital. Due to CAA safety requirements, only "Performance Class One" (twin-engined) helicopters are allowed to land on the hospital.[5]
The original hospital was built at The Octagon in 1851, and moved to the site of the present hospital in 1865.[6]
2007 Norovirus outbreak
In March 2007 two wards of the hospital were closed due to a suspected outbreak of norovirus, thought to have been brought in by a patient.[7] On 16 August 2008 the hospital was put in lockdown for one week due to a norovirus outbreak affecting 73 patients and nearly 100 staff, blocking most visitors for the duration, and postponing 2,300 procedures.[8][9][10]
Parts of the hospital are significantly dated, especially the Clinical Services Block (erected 1965) which was constructed with asbestos, as was standard construction practice at the time. The Clinical Services Block has also had significant maintenance issues, such as asbestos and leaks in the roof which allowed rain water to seep into the main operating theatres during a storm.[11] As a result of these and other issues, a significant rebuild project is underway for the reconstruction of the entire hospital, headed by Pete Hodgson, at an estimated cost of $1.2 to 1.6 billion. It is estimated to be completed by 2028.[12]
On 4 May 2018, Health Minister David Clark announced that the Government would be building a new public hospital on the site of the former Cadbury factory site and a neighbouring block that included the building occupied by Work and Income. The construction project is estimated to cost NZ$1.4 billion, would involve around a thousand workers, and is expected to finish by 2026. Clark confirmed that the Government had purchased the former Cadbury factory site from Mondelez for an undisclosed sum. While the Government has ruled out private-public partnership, Clark has told Stuff that the Government has not ruled out Iwi investment.[13][11]
Edith Statham (1853–1951) – nurse
Colin Bouwer (born 1950) – head of psychiatry and convicted criminal
Jim Mann (born 1944) – endocrinologist
^ "The Electives Network: Dunedin Hospital" . www.electives.net. Retrieved 2021-02-25.
^ "New Zealand Out-of-Hospital Major Trauma Destination Policy -- South Island Area" (PDF). National Trauma Network/Te Hononga Whētuki ā-Motu. February 2017.
^ "Dunedin Hospital" . Southern District Health Board. Retrieved 5 May 2018.
^ Houlahan, Mike (18 February 2020). "Queen Mary theatre to reopen" . Otago Daily Times.
^ a b "Dunedin Hospital Heliport aerodrome chart" (PDF). Civil Aviation Authority. Archived from the original (PDF) on 2008-10-14. Retrieved 2009-03-16.
^ "Hospitals" . 1966 Encyclopaedia of New Zealand. Retrieved 2007-11-16.
^ "Bug closes two Dunedin hospital wards" . New Zealand Herald. March 22, 2007. Retrieved 2007-11-16.
^ McLean, Elspeth (16 August 2008). "Norovirus restricts access to hospital" . Otago Daily Times. Retrieved 2008-08-17.
^ "Hospital still in lockdown amid seven new cases" . New Zealand Herald. August 17, 2008. Retrieved 2008-08-17.
^ Schofield, Edith (22 August 2008). "Dunedin Hospital to lift lockdown" . Otago Daily Times. Retrieved 2008-08-25.
^ a b "Dunedin Hospital announcement: What you need to know" . Otago Daily Times. 4 May 2018. Retrieved 4 May 2018.
^ Houlahan, Mike (11 April 2018). "Hodgson's hospital homes plan" . Otago Daily Times. Retrieved 4 May 2018.
^ McNeilly, Hamish (4 May 2018). "Popular tourist attraction Cadbury World closing to make way for $1.4 billion Dunedin Hospital" . Stuff.co.nz. Retrieved 4 May 2018.
Southern District Health Board homepage
Dunedin and Invercargill hospital collaboration


Why does Jupiter spare Deucalion and Pyrrha from the flood?
Book III recounts the foundation of which Greek city?
Who challenges Arachne to a weaving contest?
What is the theme of Book IV?
What does Ovid prophesize in the epilogue?


The World Tourism Organization (UNWTO) hosted this year's Minister's Summit at the World Travel Market (WTM) in London yesterday (6 November 2018) on the topic of Investment in Tourism Technology.
Continuing the conversation on innovation and digital transformation in tourism, which began at the celebrations for World Tourism Day 2018 – on 27 September – in Budapest, the organisation invited a panel of private investors to talk about investment in tourism technology.
It then followed this up with the ministerial segment that linked both the public and private sectors to ensure that digital transformation enhances inclusion, sustainability and competitiveness.
Both panels were moderated by CNN's business correspondent Richard Quest, anchor of Quest Means Business and focussed on innovative ideas and partnerships that can boost investment.
Also at WTM, UNWTO launched a whitepaper on the role of music in tourism development, marketing and experiences and the economic benefits of music and tourism sector partnerships, which it has produced in collaboration with Procolombia and Sound Diplomacy.
The paper, called Music is the New Gastronomy, accompanied a panel exploring the value of music tourism in depth.
The WTM has been a three-day event in London culminating today.
The need to channel tourism revenues into cultural preservation and community development was identified as a key governance challenge at the UNWTO/UNESCO cultural tourism conference, held in Istanbul, Turkey from 3 to 5 December.


text:
Timbavati River Restoration: From Wetland to Wasteland – and back
Featured, Linda Tucker, Community Development, Conservation News
Linda with Sibusiso and Harmony, the StarLion Team gather for the days planting ceremony.
By Linda Tucker and Jason A. Turner
In the ancient knowledge behind the legendary White Lions, "Timba-vati" means "Place where the StarLions came down."
In order to save these living legends in their natural endemic habitat, the Global White Lion Protection Trust has been securing the ancestral Heartlands of the White Lions for decades. Consequently, it is no surprise to learn that our land in the South – Mbube – which houses the source of the Timbavati river, was once declared a sacred site by African kings for many centuries before the Kruger was declared a National Park.
We recognize that it is essential that this river system is protected not only for mythic cultural reasons but for also critical conservation imperatives.
Our Non-Profit Organization does the conservation work for a global heritage, with limited resources but with huge heart and unstoppable determination – work that should rightfully be shouldered and funded by governments whose responsibility is to the sustainability of our wildlife heritage. Regarded as Africa's most sacred animal, we know that in protecting the White Lions, we also have to protect their natural ecosystem. Hence our motto: Lions, Land, People.
It is a travesty that high-level developers should come into this region without so much as an Environmental Impact Assessment, and ruthlessly bull-doze the ecologically sensitive head-waters of this Timbavati river system. As mentioned, these waters are regarded as a sacred river of the StarLions, with good reason: they form the life-blood to the whole body of the ecosystem, an artery all the way to and through the Kruger National Park delivering life-giving water to all the complex species who should be protected there.
First opposing this illegal development, then employing enviro-lawyers to contest it, we now are working on solutions to redress the damage of a brutal scar on the landscape which can be seen from outer space. And, like a Phoenix rising from the dust and ashes, we have a plan to restore the site. Not only restoration but more: establishing a showcase restoration project that will not only prevent similar devastation from taking place in the region but create a lasting wildlands heritage site that serves future generations of learners and indigenous healers alike. Regeneration is the 6th Law of LionHearted Leadership™. And our efforts bring our StarLion youth program together with Eco Rangers from Acorn-to-Oaks school and partners, Conservation South Africa and Hans Hoheisen, including the blessing of the traditional authorities and the traditional healers, who will benefit for generations to come from the medicinal plants being planted today.
Day 1 of the Regeneration program:
It began with a planting ceremony that brought everyone together – including a visitor group of guests led by author Elen Thompkins who were enthusiastically roped in. After carefully consulting on the ecological importance of the different species, StarLion Eco Officer Sibusiso Ngobeni gathered indigenous saplings from all our StarLion centres together Cultural Officer Harmony Khosa, focusing on those which are used for medicinal purposes by our traditional healers in Maria Khosa's lineage. But before we could take any step, we made sure we got permission from the great ancestor who guards over the StarLion River site: a giant Spirit Python who made an appearance in our dreams! You'll see the rainbow ribbons in Her honour.
6 November 2017, the first 100 trees were planted under the African sun.
Faraway in the White Lion Heartlands, we synchronized our tree planting efforts with the global Tree Sisters initiative, in which devastation sites are being replanted worldwide. What's more, Tracey van den Brand, who once did a great job of running our UK office, now drives Tree Sisters, together with figure-head Clare du Bois, and former graduate of our Academy of LionHearted Leadership™: Elizabeth Soltis, the Director of Partnerships for Tree Sisters.
Collaboration is the 7th Law of LionHearted Leadership™, and we at the Global White Lion Protection Trust excel at it! Even the cattle walking through assisting by contributing their dung as fertilizer to the young saplings!
From Wetland to Wasteland: Where once was a rich biodiversity hotspot enjoyed by a vast variety of species, the protective layer of top-soil, 2-meters deep, has been removed from century-old trees, leaving the devasted site exposed massive erosion and landslide. On this scarred landscape, the foundations of Acorn-to-Oaks High School have been built.
The illegal development: mushroomed-up without due process, Environmental Impact Assessments or a public participation process.
Scar from outer space: Google Earth reveals the scar (bottom middle).
This ecologically-sensitive landscape at the Head Waters of the Timbavati River seeps from the foothills of the Drakensberg Mountains into the lands of Mbube (meaning "LionStar") – then these wetlands flow all the way to and through the Kruger National Park, providing critical water to an endless variety of species.
One of the 100 medicinal trees planted on a devastation site – and it's only the beginning of a show-case restoration project that will leave a lasting heritage for future generations.
Earth-moving machines: bull-doze the ecologically
sensitive wetlands that feed the Head Waters of the Sacred Timbavati River.
English	 Italian	 Japanese	 Spanish

redpajama_set_name: RedPajamaCommonCrawl


text:
/**
 * TER Lego 2015 - Université Paul Sabatier
 * @author LACHERAY Benjamin, ANTOINE Kevin, MOUGEOT Matteo
 *
 */

package scanner;

import static scanner.Constantes.*;

import lejos.nxt.LightSensor;
import lejos.nxt.Motor;
import lejos.nxt.NXTRegulatedMotor;
import lejos.nxt.SensorPort;
import lejos.nxt.Sound;
import lejos.robotics.navigation.DifferentialPilot;

/**
 * Fourni des déplacements et redressements optimisés pour
 * la vitesse. Pour plus de documentation sur les méthodes,
 * voir la classe DeplacementOp
 *
 */
public class DeplacementFast extends DifferentialPilot {

	public DeplacementFast() {
		//super(wheelDiameter, trackWidth, leftMotor, rightMotor);
		super(56, 120, Motor.B, Motor.A);
	}

	public void fastHairpinTurnTo(int cote) {
		setTravelSpeed(340);
		if (cote == LEFT) {
			arc(0,90);
		} else if (cote == RIGHT) {
			arc(0,-90);
		}
	}

	public void fastRecoveryAngleWithLine() {

	    LightSensor lightLeft = new LightSensor(SensorPort.S2, true);
	    LightSensor lightRight = new LightSensor(SensorPort.S3, true);
		if (lightLeft.getNormalizedLightValue() > lightLimit) {
			Motor.B.setSpeed(180);
			Motor.B.forward();
			while (lightLeft.getNormalizedLightValue() > lightLimit) {
				Thread.yield();
			}
			Motor.B.stop();
			Sound.beep();
		} else if (lightRight.getNormalizedLightValue() > lightLimit) {
			Motor.A.setSpeed(180);
			Motor.A.forward();

			while (lightRight.getNormalizedLightValue() > lightLimit) {
				Thread.yield();
			}
			Motor.A.stop();
			Sound.beep();
		}
	}

	private void myRotateTo(NXTRegulatedMotor moteur, int vitesse, int angle) {
		moteur.resetTachoCount();

		moteur.setSpeed(vitesse);
		moteur.rotateTo(angle);

		while (moteur.isMoving()) {
			Thread.yield();
		}
	}

	public void fastRedressement(int cote) throws InterruptedException {
		int vitesse = 600; // en degré/s
		if (cote == LEFT) {
			myRotateTo(Motor.B, vitesse, -200);
			myRotateTo(Motor.A, vitesse, -200);
		} else if (cote == RIGHT) {
			myRotateTo(Motor.A, vitesse, -200);
			myRotateTo(Motor.B, vitesse, -200);
		}

		setTravelSpeed(150);
		travel(60);
	}

}

redpajama_set_name: RedPajamaGithub


text:
\section{RCAC Algorithm}

This section briefly reviews the retrospective cost adaptive control (RCAC) algorithm.
Consider a SISO PID controller with a feedforward term
\begin{align}
    u_k
        &=
            K_{{\rm p},k} z_{k-1} +
            K_{{\rm i},k} \gamma_{k-1}
            \nonumber \\ &\quad +
            K_{{\rm d},k} (z_{k-1} - z_{k-2}) +
            K_{{\rm ff},k} r_k
            ,
    \label{eq:uk_PID}
\end{align}
where $K_{{\rm p},k}, K_{{\rm i},k}, K_{{\rm d},k}, $ and $K_{{\rm ff},k}$ are time-varying gains to be optimized,
$z_k$ is an error variable,
$r_k$ is the feedforward signal,
and, for all $k\ge0$,
\begin{align}
    \gamma_k
        \stackrel{\triangle}{=}
            \sum_{i=0}^{k} g(z_{i}).
\end{align}
Note that the integrator state is computed recursively using $\gamma_k = \gamma_{k-1} + g(z_{k-1})$.
For all $k\ge0$,
the control law can be written as
\begin{align}
    u_k
        =
            \phi_k \theta_k,
    \label{eq:uk_reg}
\end{align}
where
the regressor $\phi_k$
and
the controller gains $\theta_k$
are
\begin{align}
    \phi_k
        \stackrel{\triangle}{=}
            \left[ \begin{array}{c}
                z_{k-1} \\
                \gamma_{k-1} \\
                z_{k-1} - z_{k-2} \\
                r_k
            \end{array} \right]^{\rm T}, \quad
    \theta_k
        \stackrel{\triangle}{=}
            \left[ \begin{array}{c}
                K_{{\rm p},k} \\
                K_{{\rm i},k} \\
                K_{{\rm d},k} \\
                K_{{\rm ff},k}
            \end{array} \right] .

    \label{eq:phi_theta_def}
\end{align}
Note that the P, PI, or PID controllers can be parameterized by appropriately defining $\phi_k$ and $\theta_k.$
Various MIMO controller parameterizations are shown in \cite{goel_2020_sparse_para}.

To determine the controller gains $\theta_k$, let $\theta \in {\mathbb R}^{l_\theta}$, and consider the \textit{retrospective performance variable} defined by
\begin{align}
    \hat{z}_{k}(\theta)
        \stackrel{\triangle}{=}
            z_k +
            \sigma (\phi_{k-1} \theta - u_{k-1}),
    \label{eq:zhat_def}
\end{align}
where $\sigma \in {\mathbb R}.$
The sign of $\sigma$ is the sign of the leading numerator coefficient of the transfer function from $u_k$ to $z_k.$
Furthermore, define the \textit{retrospective cost function} $J_k \colon {\mathbb R}^{l_\theta} \to [0,\infty)$ by
\begin{align}
    J_k(\theta)
        &\stackrel{\triangle}{=}
            \sum_{i=0}^k
                \hat{z}_{i}(\theta) ^{\rm T}
                R_z
                \hat{z}_{i}(\theta)
                 +
                (\phi_k \theta)^{\rm T}
                R_u
                (\phi_k \theta)
                \nonumber \\ &\quad \quad +
                (\theta-\theta_0)^{\rm T}
                P_0^{-1}
                (\theta-\theta_0),
    \label{eq:RetCost_def}
\end{align}
where $\theta_0\in{\mathbb R}^{l_\theta}$ is the initial vector of PID gains and $P_0\in{\mathbb R}^{l_\theta\times l_\theta}$ is positive definite.

\begin{proposition}
    Consider \eqref{eq:uk_reg}--\eqref{eq:RetCost_def},
    where $\theta_0 \in {\mathbb R}^{l_\theta}$ and $P_0 \in {\mathbb R}^{l_\theta \times l_\theta}$ is positive definite.
    Furthermore, for all $k\ge0$, denote the minimizer of $J_k$ given by \eqref{eq:RetCost_def} by
    \begin{align}
        \theta_{k+1}
            \stackrel{\triangle}{=}
                \underset{ \theta \in {\mathbb R}^n  }{\operatorname{argmin}} \
                J_k({\theta}).
        \label{eq:theta_minimizer_def}
    \end{align}
    Then, for all $k\ge0$, $\theta_{k+1}$ is given by
    \begin{align}
        \theta_{k+1}
            &=
                \theta_k  -
                 \sigma P_{k+1}\phi_{k-1}^{\rm T} R_z
                 [ z_k + \sigma(\phi_{k-1} \theta_k - u_{k-1}) ]
                 \\ &\quad \quad
                 -
                 P_{k+1}\phi_{k}^{\rm T}
                 R_u \phi_{k} \theta_k
                 , \label{eq:theta_update}
    \end{align}
    where
    \begin{align}
        P_{k+1}
            &=
                P_{k}
                -
                P_k
            \Phi_k ^{\rm T}
            \left(
                \bar R ^{-1} +
                \Phi_k
                P_k
                \Phi_k ^{\rm T}
            \right)^{-1}
            \Phi_k,
        \label{eq:P_update_noInverse}
    \end{align}
    and
    \begin{align}
        \Phi_k
            \stackrel{\triangle}{=}
            \left[ \begin{array}{c}
                \sigma \phi_{k-1} \\
                \phi_k
            \end{array} \right],
        \quad
        \bar R
            \stackrel{\triangle}{=}
                \left[ \begin{array}{cc}
                    R_z & 0 \\
                    0   & R_u
                \end{array} \right].
    \end{align}

\end{proposition}
\begin{proof}
See \cite{AseemRLS}.
\end{proof}

Finally, the control is given by
\begin{align}
    u_{k+1} = \phi_{k+1} \theta_{k+1}.
\end{align}
\section{Introduction}

Autonomous flight control of an aircraft under rapidly changing conditions depends on an effective autopilot that can control the aircraft in uncertain environments and without detailed models.
The autopilot for fixed-wing aircrafts typically consists of a set of trim commands along with low-level controllers to track intermediate commands.
The trim conditions for an aircraft can be computed by solving nonlinear algebraic equations for trim equilibria \cite{mcclamroch2011steady}, but a detailed knowledge of aircraft aerodynamics is required.
Moreover, for low-cost aircrafts that are usually repaired or modified onsite, the true aerodynamic properties may be different from nominal aerodynamics.
Consequently, a fixed-gain autopilot may not be able to maintain performance in rapidly changing environment or under failure conditions such as chipped wings or stuck actuators.
In this scenario, an adaptive autopilot may be able to compensate for the lost performance by updating the autopilot gains accordingly.
With these motivations in mind, this paper explores the use of an in situ learning technique to modify the autopilot during the flight.

Several adaptive control techniques have been investigated for the problem of fixed-wing aircraft control
\cite{nguyen2006dynamics}.
A sliding mode fault-tolerant tracking control scheme was used for control of a fixed-wing UAV under actuator saturation and state constraints in \cite{9262225, 9476716}.
A backstepping algorithm was used  in \cite{hirano2019controller} to design a nonlinear flight controller for a fixed-wing UAV with thrust vectoring.
An MRAC-based control technique was used to augment the control system to improve the dynamic performance of a fixed-wing aircraft in \cite{9189264}.
However, these techniques rely on the availability of a sufficiently detailed model for the control system synthesis.
In contrast, this paper uses the the retrospective cost adaptive control (RCAC) algorithm to learn the autopilot from the measured data in situ.
RCAC is a digital adaptive control technique that is applicable to stabilization, command-following, and disturbance-rejection problems.
Instead of relying on a model of the system, RCAC uses the past measured data and past applied input to recursively optimize the controller gains.
RCAC is described in detail in \cite{rahmanCSM2017} and its extension to digital PID control is given in \cite{rezaPID}.
The application of the RCAC algorithm for a multicopter autopilot are described in \cite{goel_adaptive_pid_2021,quadtuner2021}.

The contribution of this paper is the development of an adaptive digital autopilot, and comparison of its performance with a well-tuned fixed-gain autopilot under nominal conditions, rapidly changing conditions, and actuator failure.
In particular, this paper presents the potential advantages of an adaptive autopilot by investigating two scenarios.
In the first scenario, a well-tuned fixed-gain controller is detuned by scaling all of the gains by a small factor, and it is shown that the adaptive autopilot is able to compensate for the detuned gains by learning the necessary gains.
In the second scenario, the aircraft is simulated with a frozen aileron, thus emulating an actuator failure condition, and it is shown that the adaptive autopilot  improves the trajectory-tracking performance.

The paper is organized as follows:
Section \ref{sec:notation} defines the notation used in this paper, %
Section \ref{sec:PX4_autopilot} reviews the autopilot architecture implemented in the PX4 flight stack,
Section \ref{sec:RCAC} reviews the retrospective cost adaptive algorithm,
Section \ref{sec:adaptiveAugmentation} presents the adaptive augmentation of autopilot,
Section \ref{sec:flight_tests} presents the simulation tests,
and finally,
Section \ref{sec:conclusions} concludes the paper with a summary and future research directions.

\section{Notation}
\label{sec:notation}
Let $\rm F_E$ denote an Earth-fixed frame such that $ {\hat k}_{\rm E}$ is aligned with gravity $\vect g.$
Let $\rm F_{AC}$ denote an aircraft-fixed frame such that $ {\hat \imath}_{\rm AC}$ is aligned with the fuselage,
$ {\hat \jmath}_{\rm AC}$ is along the wing, and
$ {\hat k}_{\rm AC}$ is chosen to complete the right-handed frame.
Note that $ {\hat k}_{\rm AC}$ points vertically down.
Next, let ${\rm c}$ denote the center of mass of the aircraft, and let $w$ be an point fixed on Earth.
The coordinates of the aircraft relative to $w$ in the Earth frame are denoted by $r \stackrel{\triangle}{=} \vect r_{{\rm c}/w}\resolvedinFrame{E} \in {\mathbb R}^3.$
The velocity of the aircraft relative to $w$ in the Earth frame is  $ v\stackrel{\triangle}{=}  \vect v_{{\rm c}/w/{\rm E}}\resolvedinFrame{E} \in {\mathbb R}^3.$
Let $\Theta, \Psi,$ and $\Phi$ denote the pitch, azimuth, and the roll angle of the aircraft.
The angular velocity of $\rm F_{AC}$ relative to  $\rm F_E$ in the aircraft-fixed frame is given by $\omega \stackrel{\triangle}{=} \vect \omega_{{\rm AC} / {\rm E}}\resolvedinFrame{\rm AC} \in {\mathbb R}^3.$
The angular acceleration of $\rm F_{AC}$ relative to  $\rm F_E$ in the aircraft-fixed frame is given by $\alpha \stackrel{\triangle}{=} \vect \alpha_{{\rm AC} / {\rm E}}\resolvedinFrame{\rm AC} \in {\mathbb R}^3.$
The measurement of the variable $x$ is denoted by $x_{\rm m}$, and the setpoint for the variable $x$ is denoted by $x_{\rm s}.$
Finally, let $e_3 \stackrel{\triangle}{=} \left[ \begin{array}{c c c} 0 & 0 & 1 \end{array} \right]^{{\rm T}}.$

\section{PX4 Autopilot}
\label{sec:PX4_autopilot}
In this section, the control system implemented in the PX4 autopilot for fixed-wing aircraft is described. %
The control system consists of a mission planner and two cascaded controllers in nested loops as shown in Figure  \ref{fig:PX4_autopilot_nested_loop}.
The mission planner generates position setpoints based on the user-defined waypoints.

\begin{figure}[h]
    \centering
    \resizebox{\columnwidth}{!}{
    \begin{tikzpicture}[auto, node distance=2cm,>=latex',text centered]

        \node [smallblock, minimum height=3em, text width=1.6cm] (Mission) {\small Mission Planner};
        \node [smallblock, minimum height=3em, right = 5em of Mission, text width=1.6cm] (Pos_Cont) {\small Position Controller};
        \node [smallblock, minimum height=3em, below right = 1.75em and -2.25 em of Pos_Cont,text width=1.6cm] (Att_Cont) {\small Attitude Controller};
        \node [smallblock, minimum height=3em, text width=1.6cm, minimum width = 5.5em,  right = 4em of Pos_Cont] (FWAircraft) {\small Fixed-Wing Aircraft};

        \draw [->] (Mission) -- node[above, xshift = -0.05 em, yshift = 0.1em]{ {}$r_{\rm s}, V_{{\rm T}, {\rm s}}$} (Pos_Cont);
        %
        \draw [->] (Pos_Cont.-10) -| ([xshift = 0.75em, yshift = -2em]Pos_Cont.-10) -| node  [xshift = 3.15em, yshift = 1em] {\small {}$\begin{array}{c} \Phi_{{\rm s}} , \\ \Theta_{{\rm s}} \end{array}$} ([xshift = -0.75em]Att_Cont.west) -- (Att_Cont.west);
        \draw [->] (Pos_Cont.10) -- node [above, xshift = 0.05em, yshift = 0.1 em] { \small{}$T _{\rm s}$} (FWAircraft.170);
        \draw [->] (Att_Cont.0) -- +(0.15,0) |- node [below, xshift = 0.7 em, yshift = -2 em]{\small {}$\alpha_{{\rm s}}$}(FWAircraft.190);
        %
        \draw [->] (FWAircraft.0) -- +(.4,0) |- node[below,xshift = -6em, yshift = 0.05em]{ \small {} $r_{{\rm m}}, V_{{\rm T}}, V_{{\rm G}}$} ([xshift = -1.5em, yshift = -7.8 em]Pos_Cont.south) --  ([xshift = -1.5em]Pos_Cont.south);
        %
        \draw [->] (FWAircraft.350) -- +(0.2,0) |- node[below,xshift = -5em]{ \small {} $ \Phi_{{\rm m}}, \Theta_{{\rm m}}, V_{{\rm T}}, V_{{\rm I}} , \omega_{{\rm m}}$} ([yshift = -0.75 em]Att_Cont.south) -- (Att_Cont.south);
        %
         \draw [->] (FWAircraft.10) -- +(.6,0) |- node[below,xshift = -6em, yshift = -0.05em]{ \small {} $V_{{\rm G}}$} ([yshift = -10 em]Mission.south) --  (Mission.south);
    \end{tikzpicture}
    }
    \vspace{-2em}\caption{\footnotesize PX4 autopilot architecture. }
    \label{fig:PX4_autopilot_nested_loop}
\end{figure}

The outer loop, also called the position controller, consists of two decoupled controllers for the longitudinal and the lateral motion of the aircraft, and is shown in Figure \ref{fig:PX4_autopilot_outer_loop}.
The longitudinal controller is based on the total energy control system (TECS) described in \cite{bruce1986,faleiro1999,lambregts2013,Argyle2016} and the lateral controller is based on the guidance law described in \cite{park2004}.
The input to the position controller are the true airspeed setpoint $V_{{\rm T}, {\rm s}},$ the position setpoint $r_{\rm s},$ the true airspeed $V_{{\rm T}},$ the position measurement $r_{\rm m},$ and the ground velocity $V_{{\rm G}}.$
Note that the TECS input include the altitude setpoint $h_{\rm s} \stackrel{\triangle}{=} e_3^{\rm T} r_{\rm s},$ and the altitude measurement $h _{\rm m} \stackrel{\triangle}{=} e_3^{\rm T} r_{\rm m}.$
The longitudinal controller generates the thrust and the pitch setpoint, and the lateral controller generates the roll setpoint.
The output of the position controller is thus the thrust setpoint $T_{\rm s}$ and the attitude setpoint ($\Phi_{\rm s}, \Theta_{\rm s},$ since $\Psi_{\rm s}$ is not required by the attitude controller).

\begin{figure}[h]
    \centering
    \resizebox{0.8\columnwidth}{!}{
    \begin{tikzpicture}[auto, node distance=2cm,>=latex']
        %
        \node[smallblock, minimum width = 6em, minimum height = 7 em] (TECS) {TECS};
        %

        %
        \node[smallblock, below = 4.5em of TECS.center, minimum width = 2.5em, minimum height = 3 em] (L1C) {$\begin{array}{c}{\rm Lateral} \\ {\rm Controller}\end{array}$};
        %
        \node[smallblock, below left = 0.05em and 7em of TECS.center, minimum width = 1em, minimum height = 1 em] (r2h1) {\small $e_3^{\rm T}$};
        %
        \node[smallblock, below left = 2em and 7em of TECS.center, minimum width = 1em, minimum height = 1 em] (r2h2) {\small $e_3^{\rm T}$};
        %
        \draw[->] (r2h1.east) -- node[above, xshift = -0.1em]{\small$h_{{\rm s}}$} ([yshift = -0.9em]TECS.west);
        %
        \draw[->] (r2h2.east) -- node[above]{\small$h_{{\rm m}}$} ([yshift = -2.875em]TECS.west);
        %
        \draw[->] ([xshift = -4.5em]r2h1.west) -- node[above, xshift = -1.5em]{\small$r_{\rm s}$} (r2h1.west);
        %
        \draw[->] ([xshift = -4.5em]r2h2.west) -- node[above, xshift = -1.5em]{\small$r_{\rm m}$} (r2h2.west);
        %
        \draw[->] ([xshift = -4em, yshift = 2.675em]TECS.west) -- node[above, xshift = -0.1em]{\small$V_{{\rm T}, {\rm s}}$} ([yshift = 2.675em]TECS.west);
        %
        \draw[->] ([xshift = -4em, yshift = 1em]TECS.west) -- node[above]{\small$V_{{\rm T}}$} ([yshift = 1em]TECS.west);
        %
        \draw[->] ([xshift = -4em, yshift = 0.75em]L1C.west) -- node[above]{\small$V_{{\rm G}}$} ([yshift = 0.75em]L1C.west);
        %
        \draw[-] ([xshift = -1.5em]r2h1.west)--([xshift = -1.5em, yshift = -1.75em]r2h1.west);
        \draw ([xshift = -1.5em, yshift = -2.25 em]r2h1.west) arc (270:90:0.25em);
        \draw[->] ([xshift = -1.5em, yshift = -2.25em]r2h1.west) |- (L1C.west);
        %
        \draw[->] ([xshift = -2.5em]r2h2.west) |- ([yshift = -0.75em]L1C.west);
        %
        \draw[->] ([yshift = 1.7em]TECS.east) -- node[above]{\small $T_{{\rm s}}$} ([xshift = 3em, yshift = 1.7em]TECS.east);
        %
        \draw[->] ([yshift = -1.7em]TECS.east) --  node[above]{\small $\Theta_{{\rm s}}$} ([xshift = 3em, yshift = -1.7em]TECS.east);
        %
        \draw[->] (L1C.east) --  node[above]{\small $\Phi_{{\rm s}}$} ([xshift = 3em]L1C.east);
        %
    \end{tikzpicture}
    }
    \caption{\footnotesize PX4 autopilot position controller. }
    \label{fig:PX4_autopilot_outer_loop}
\end{figure}

The inner loop, also called the attitude controller, consists of two cascaded controllers, and is shown in Figure \ref{fig:PX4_autopilot_inner_loop}.
The first controller uses the pitch and roll errors and a proportional control law to generate the pitch-rate and roll-rate setpoints.
In particular, the pitch-rate setpoint $\dot{\Theta}_{{\rm s}}$ and the roll-rate setpoint $\dot{\Phi}_{{\rm s}} $ are given by
\begin{align}
    \dot{\Theta}_{{\rm s}}
        &=
            k_\theta(\Theta_{{\rm s}} - \Theta_{{\rm m}})
    \label{eq:pitch_rate_P}
        , \\
    \dot{\Phi}_{{\rm s}}
        &=
            k_\phi (\Phi_{{\rm s}} - \Phi_{{\rm m}}),
    \label{eq:Roll_rate_P}
\end{align}
where $k_{\theta}, k_{\phi}$ are the scalar gains.
The yaw-rate is computed algebraically by
\begin{align}
    \dot{\Psi}_{{\rm s}}

        = \frac{g \tan\Phi_{{\rm s}} \cos\Theta_{{\rm s}}}{V_{{\rm T}}}
    \label{eq:coordinated_turn}
\end{align}
to ensure coordinated turn.
The body-fixed angular-velocity setpoint $\omega_{\rm s}
$ is given by
\begin{align}
    \omega_{\rm s}

        &=
            S(\Theta_{{\rm m}}, \Phi_{{\rm m}})
            \begin{bmatrix}
                \dot{\Phi}_{{\rm s}} \\ \dot{\Theta}_{{\rm s}} \\ \dot{\Psi}_{{\rm s}}
            \end{bmatrix},
    \label{eq:e2omega}
\end{align}
where
\begin{align}
    S(\theta, \Phi)
        \stackrel{\triangle}{=}
    \begin{bmatrix}
        1 & 0 & \sin \Theta \\
        0 & \cos \Phi & \sin \Phi \cos \Theta \\
        0 & -\sin\Phi & \cos\Phi \cos\Theta
    \end{bmatrix}.
\end{align}

Next, a feedforward and a PI control law generates the anglular-acceleration setpoint $\alpha_s
$.
In particular, $\alpha_s $ is given by
\begin{align}
    \alpha_s
        &=
            \frac{V_{{\rm T}, 0}}{V_{{\rm T}}} G_{\omega,{\rm ff}}
            \omega_{\rm s}+
            \left(\frac{V_{{\rm I},0}}{V_{{\rm I}}}\right)^2 G_{\omega,{\rm PI}}({\textbf{\textrm{q}}})
            \left( \omega_{\rm s} - \omega_{\rm m}
            \right), \label{eq:alpha_s}
\end{align}
where $G_{\omega,{\rm ff}} = k_{\omega, \rm ff} $ is a proportional control law,
$G_{\omega,{\rm PI}}({\textbf{\textrm{q}}})  = k_{\omega, {\rm P}} + \dfrac{k_{\omega, {\rm I}}}{\textbf{q}-1}$ is a PI control law,
$V_{{\rm I}}$ is the indicated airspeed,
and $V_{{\rm T},0}$ and $V_{{\rm I},0}$ are the true airspeed and the indicated airspeed at trim conditions respectively, which are aircraft parameters.
Note that
${\textbf{\textrm{q}}}$ is the forward-shift operator,
$k_{\omega, \rm ff}, $
$k_{\omega, \rm P},$ and
$k_{\omega, \rm I}$ are $3\times 3$ diagonal matrices, and are thus parameterized by 9 scalar gains.
Finally, using the angular-acceleration setpoint, the actuator deflections are computed using control allocation methods.

\begin{figure}[h]
    \centering
    \resizebox{\columnwidth}{!}{
    \begin{tikzpicture}[auto, node distance=2cm,>=latex']
    %
    \node[smallblock, minimum width = 2.5em, minimum height = 4 em] (e2q) { \eqref{eq:e2omega}};
    %
    \node[smallblock, above left = -0.5em and 4em of e2q.center, minimum width = 2.5em, minimum height = 2.5em] (G_E) {\eqref{eq:pitch_rate_P}, \eqref{eq:Roll_rate_P}};
    %
    \node[smallblock, below left = 1.5em and 4em of e2q.center, minimum width = 2.5em, minimum height = 2.5em] (tc) {\eqref{eq:coordinated_turn}};
    %
    \node[sum, left = 2.5em of G_E.center] (suml1){};
    \node[draw = none] at (suml1.center) {$+$};
    %

    %
    \node[sum, right = 2.5 em of e2q] (sumr1){};
    \node[draw = none] at (sumr1.center) {$+$};
    %
    \node[smallblock, right = 1em of sumr1, minimum width = 2.5em, minimum height = 1.75 em] (G_PI) {$G_{\omega, {\rm PI}}$};
    %
    \node[smallblock, above = 1em of G_PI, minimum width = 2.5em, minimum height = 1.75 em] (G_FF) {$G_{\omega, {\rm FF}}$};
    %
    \node[smallblock, right = 1em of G_PI, minimum width = 2.5em, minimum height = 1.75 em] (sc) {\eqref{eq:alpha_s}};
    %
    \draw [->] (sc.east) -- ([xshift = 1.5em]sc.east) node [above, xshift=-0.4 em] { {}$\alpha_s$};
    %

    \draw[->]([yshift = -0.25em]G_E.east) -- node[above]{ {} $\begin{bmatrix} \dot{\Phi}_{{\rm s}} \\ \dot{\Theta}_{{\rm s}} \end{bmatrix}$}([yshift = 0.5em]e2q.west);
    \draw[->](tc.east)-|([xshift = -2em, yshift = -1.25em]e2q.west)-- node[above, xshift = -0.35 em]{ {}$\dot{\Psi}_{{\rm s}}$} ([yshift = -1.25em]e2q.west);

    %
    \draw[->](suml1.east) -- (G_E.west);

    \draw[->]([xshift = -0.75 em]suml1.west) |- ([yshift = 0.5em]tc.west);
    \draw[->]([xshift = -5.5em, yshift = -0.5em]tc.west) -- node[above, xshift = -2em]{ {}$V_{{\rm m}}$} ([yshift = -0.5em]tc.west);
    \draw[->]([xshift = -3.25em]suml1.west) -- node[above, xshift = -1em]{ {}$\begin{bmatrix}\Phi_{{\rm s}} \\ \Theta_{{\rm s}}\end{bmatrix}$} (suml1.west);
    %
    \draw[->]([yshift = 1em]suml1.north) -- node[xshift = -1.4 em, yshift = 1.75em]{ {}$\begin{bmatrix}\Phi_{{\rm m}} \\ \Theta_{{\rm m}} \end{bmatrix}$} node[xshift = -0.15em, yshift = -0.05em]{$-$} (suml1.north);
    %
    \draw[->](e2q.east)--node[above, xshift = -0.4em]{ {}$\omega_{{\rm s}}$}(sumr1.west);
    %
    \draw[->](sumr1.east) -- (G_PI.west);
    \draw[->]([yshift = -1em]sumr1.south) -- node[xshift = 1em, yshift = -1em]{ {}$\omega_{{\rm m}}$} node [xshift = 1.25em, yshift = -0.1em]{$-$} (sumr1.south);
    %
    \draw[->]([xshift = 1.75em]e2q.east) |- (G_FF.west);
    %
    \draw[->](G_FF.east)-|

    (sc.north);
    %
    \draw[->](G_PI.east) --

    (sc.west);
    %
    \draw[->]([yshift = -1em]sc.south) -- node[xshift = 1.75em, yshift = -1.25em]{ {}$V_{{\rm T}}, V_{{\rm I}}$} (sc.south);
    \end{tikzpicture}
    }
    \caption{\footnotesize PX4 autopilot attitude controller.}
    \label{fig:PX4_autopilot_inner_loop}
\end{figure}

The fixed-wing autopilot thus consists of 11 gains.
In practice, these 11 gains are manually tuned and require considerable expertise.

\section{RCAC algorithm}
\label{sec:RCAC}
\input{RCAC_section}

\section{Adaptive PX4 Autopilot}
\label{sec:adaptiveAugmentation}
This section describes the adaptive autopilot, which is constructed by augmenting the fixed-gain autopilot described in Section \ref{sec:PX4_autopilot}.
In particular, each fixed-gain control law is modified by adding an adaptive control law, which is updated by the retrospective cost adaptive control (RCAC) algorithm described in Section \ref{sec:RCAC}.
The output of the modified controller is thus given by the sum of the fixed-gain control law and the adaptive control law, as shown in Figure \ref{fig:Augmented_PX4_autopilot_inner_loop}.

\begin{figure}[h]
    \centering
    \resizebox{\columnwidth}{!}{
    \begin{tikzpicture}[auto, node distance=2cm,>=latex']
    %
    \node[smallblock, minimum width = 2.5em, minimum height = 4 em] (e2q) { \eqref{eq:e2omega}};
    %
    \node[smallblock, above left = -0.5em and 6.5em of e2q.center, minimum width = 4em, minimum height = 2.5em] (G_E) {\eqref{eq:pitch_rate_P}, \eqref{eq:Roll_rate_P}};
    %
    \node[smallblock, below left = 4.9em and 6.5em of e2q.center, minimum width = 2.5em, minimum height = 2.5em] (tc) {\eqref{eq:coordinated_turn}};
    %
    %
    \node[sum, left = 4em of G_E.center] (suml1){};
    \node[draw = none] at (suml1.center) {$+$};
    %
    \node[sum, below right = -0.075em and 1.65em of G_E.east] (suml2){};
    \node[draw = none] at (suml2.center) {$+$};
    %
    \node[sum, right = 3em of e2q] (sumr1){};
    \node[draw = none] at (sumr1.center) {$+$};
    %
    \node [right = 0.3 em of suml1.east] (suml1_hook) {};
    \draw [->] (suml1_hook.center) -- +(0,-1.8) -- +(.5,-1.8) -- +(1.7,-.6);
    \node[smallblock, fill=green!20, below = 1em of G_E.south, minimum width = 0.5em, minimum height = 2 em, inner sep=0.25pt](G_E_adap){ {}$\begin{array}{c} {\rm Adaptive} \\ \eqref{eq:adaptive_pitch_rate_P}, \eqref{eq:adaptive_roll_rate_P} \end{array}$};
    \draw[->] (suml1_hook.center)|-(G_E_adap.west);
    %
    %
    \node[smallblock, right = 3em of sumr1, minimum width = 2.5em, minimum height = 1.75 em] (G_PI) {$G_{\omega, {\rm PI}}$};
    %
    \node [left = 1.25 em of G_PI.west] (G_PI_hook) {};
    \draw [->] (G_PI_hook.center) -- +(0,-2.4) -- +(.5,-2.4) -- +(1.7,-1.2);
    \node[smallblock, fill=green!20, below = 3em of G_PI.south, minimum width = 0.5em, minimum height = 2 em, inner sep=0.25pt](G_PI_adap){ {}$\begin{array}{c} {\rm Adaptive} \\ \eqref{eq:alpha_s_adaptive} \end{array}$};
    \draw[->] (G_PI_hook.center)|-(G_PI_adap.west);
    %
    %
    \node[smallblock, above = 1em of G_PI, minimum width = 2.5em, minimum height = 1.75 em] (G_FF) {$G_{\omega, {\rm FF}}$};
    %

    %
    \node[smallblock, right = 1em of G_PI, minimum width = 2.5em, minimum height = 1.75 em] (sc) {\eqref{eq:alpha_s}};
    %
    \node[sum, right = 1em of sc] (sumPI){};
    \node[draw = none] at (sumPI.center) {$+$};
    %
    \draw [->] (sumPI.east) -- ([xshift = 1.5em]sumPI.east) node [above, xshift=-0.4 em] { {}$\alpha_s$};
    %
    \draw[->]([yshift = -0.25em]G_E.east) -- (suml2.west);
    %
    \draw[->](suml2.east) -- node[above]{ {} $\begin{bmatrix} \dot{\Phi}_{{\rm s}} \\ \dot{\Theta}_{{\rm s}} \end{bmatrix}$}([yshift = 0.5em]e2q.west);
    %
    \draw[->](G_E_adap.east) -| (suml2.south);
    %
    \draw[->](tc.east)-|([xshift = -2em, yshift = -1.25em]e2q.west)-- node[above, xshift = -0.15 em]{ {}$\dot{\Psi}_{{\rm s}}$} ([yshift = -1.25em]e2q.west);
    %
    \draw[->](suml1.east) -- (G_E.west);
    \draw[->]([xshift = -0.75 em]suml1.west) |- ([yshift = 0.7em]tc.west);
    \draw[->]([xshift = -6.4em, yshift = -0.7em]tc.west) -- node[above, xshift = -2.5em]{ {}$V_{{\rm m}}$} ([yshift = -0.7em]tc.west);
    \draw[->]([xshift = -3.25em]suml1.west) -- node[above, xshift = -1em]{ {}$\begin{bmatrix}\Phi_{{\rm s}} \\ \Theta_{{\rm s}}\end{bmatrix}$} (suml1.west);
    %
    \draw[->]([yshift = 1em]suml1.north) -- node[xshift = -1.6 em, yshift = 1.9em]{ {}$\begin{bmatrix}\Phi_{{\rm m}} \\ \Theta_{{\rm m}} \end{bmatrix}$} node[xshift = -0.15em, yshift = 0.1em]{$-$} (suml1.north);
    %
    \draw[->](e2q.east)--node[above, xshift = -0.65em]{ {}$\omega_{{\rm s}}$}(sumr1.west);
    %
    \draw[->](sumr1.east) -- (G_PI.west);
    \draw[->]([yshift = -1em]sumr1.south) -- node[xshift = 1em, yshift = -1.1em]{ {}$\omega_{{\rm m}}$} node [xshift = 1.4em, yshift = -0.1em]{$-$} (sumr1.south);
    %
    \draw[->]([xshift = 2em]e2q.east) |- (G_FF.west);
    %

    %
    \draw[->](G_FF.east)-|

    (sc.north);
    %
    \draw[->](G_PI_adap)-|(sumPI.south);
    \draw[->](G_PI.east)--(sc.west);
    %
    \draw[->](sc.east) --

    (sumPI.west);
    %
    \draw[->]([yshift = -1em]sc.south) -- node[xshift = 1.75em, yshift = -1.25em]{ {}$V_{{\rm T}}, V_{{\rm I}}$} (sc.south);
    \end{tikzpicture}
    }
    \caption{\footnotesize Adaptive PX4 autopilot attitude controller.}
    \label{fig:Augmented_PX4_autopilot_inner_loop}
\end{figure}

The bank and elevation rate setpoints $\dot{\Phi}_{{\rm s}}, \dot{\Theta}_{{\rm s}}$ in the adaptive autopilot are given by
\begin{align}
    \dot{\Theta}_{{\rm s}}
        &=
            k_\theta(\Theta_{{\rm s}} - \Theta_{{\rm m}})
            +
            u_\Theta
        \label{eq:adaptive_pitch_rate_P}
        , \\
    \dot{\Phi}_{{\rm s}}
        &=
            k_\phi (\Phi_{{\rm s}} - \Phi_{{\rm m}})
            +
            u_\Phi
            ,
        \label{eq:adaptive_roll_rate_P}
\end{align}
where $u_\Theta$ and $u_\Phi$ are computed by the RCAC algorithm.
Note that $u_\Theta$ and $u_\Phi$ are scalars.
Similarly, the angular acceleration setpoint in the adaptive autopilot is given by
\small
\begin{align}
    \alpha_s
        &=
            \frac{V_{{\rm T}, 0}}{V_{{\rm T}}} G_{\omega,{\rm ff}}
            \omega_{\rm s}

            \nonumber \\
            & \quad +
            \left(\frac{V_{{\rm I},0}}{V_{{\rm I}}}\right)^2 G_{\omega,{\rm PI}} ({\textbf{\textrm{q}}})
            \left( \omega_{\rm s} - \omega_{\rm m}
            \right)
            +
            u_{\omega, \rm PI}, \label{eq:alpha_s_adaptive}
\end{align}
\normalsize
where
$u_{\omega, \rm PI}$ is computed by the RCAC algorithm.
Note that $ u_{\omega, \rm PI} \in {\mathbb R}^3,$ and each component of $u_{\omega, \rm PI}$ is updated by RCAC, where the error variable is the corresponding error term.

\section{Simulation Results}
\label{sec:flight_tests}

This section investigates the performance of the adaptive autopilot and compares it to the performance of the fixed-gain autopilot with stock PX4 gains.
The fixed-wing aircraft is simulated in Gazebo.
In particular, the standard plane model \footnote{\href{https://docs.px4.io/master/en/simulation/gazebo_vehicles.html\#standard_plane}{Gazebo standard plane simulator}} provided by the PX4 developers is used.
The default controller gains and the actuator constraints in PX4 are specified in the
\verb|fw_att_control_params.c|
\footnote{\href{https://github.com/JAParedes/PX4-Autopilot/tree/RCAC_FW_dev}{https://github.com/JAParedes/PX4-Autopilot/tree/RCAC\_FW\_dev}}.
Note that the results in this paper are based on PX4 version V1.10.0dev.

The default controller gains in PX4 are well-tuned for the Gazebo model considered in this paper.
To investigate the potential improvements in the performance, the default controller gains in PX4 are multiplied by a scalar $\alpha_{\rm d}$ to degrade the performance of the autopilot.
This is equivalent to the case of poor initial choice of controller gains.
The baseline performance is obtained with $\alpha_{\rm d}=1$.
A value of $\alpha_{\rm d} \neq 1$ is assumed to degrade the performance of the autopilot.
In the case where $\alpha_{\rm d} = 0,$ the fixed-gain autopilot is completely switched off, and the adaptive autopilot learns the controller gains in-situ.
Table \ref{tab:RCPE_variables_SITL} lists the hyperparameters used by RCAC.
Note that the RCAC hyperparameters are not changed as $\alpha_{\rm d}$ is varied.

Figure \ref{fig:flightPathFW} shows the trajectory of the fixed-wing aircraft for various values of $\alpha_{\rm d}$ with both the fixed-gain and the adaptive autopilot.
The baseline performance is obtained with $\alpha_{\rm d}=1,$ and in this case, adaptive autopilot does not affect the performance.
For $\alpha_{\rm d}=0.5,$ the trajectory following response degrades substantially for the fixed-gain autopilot, and in this case, the adaptive autopilot recovers the baseline performance.
Finally, the adaptive autopilot is also able to learn the gains in situ, in the case where the fixed-gain autopilot is completely switched off, that is, $\alpha_{\rm d}=0.$
Figure \ref{fig:thetaPlot} shows the gains adapted by RCAC for the three values of $\alpha_{\rm d}. $
Note that as the fixed-gain controller is detuned, RCAC compensates by providing larger values of gains.

\begin{table}[h]
    \caption{\footnotesize RCAC hyperparameters in the adaptive autopilot.

    }

    \label{tab:RCPE_variables_SITL}
    \centering
    \renewcommand{\arraystretch}{1.2}
    \begin{tabular}{|c|l|l|}
        \hline
        \multicolumn{1}{|c|}{\textbf{Controller}}  & \multicolumn{1}{|c|}{${P_0}$}  & \multicolumn{1}{|c|}{${R_u}$}
        \\ \hhline{|=|=|=|}
        \eqref{eq:adaptive_pitch_rate_P}, $\theta_\Theta$
        & $0.01$ & $0.001$
        \\ \hline
        \eqref{eq:adaptive_roll_rate_P}, $\theta_\Phi$ & $1$ & $0.001$
        \\ \hline

        \eqref{eq:alpha_s_adaptive}, $\theta_{\dot \Theta}$

        & $1000$ & $0.1$
        \\ \hline
        \eqref{eq:alpha_s_adaptive}, $\theta_{\dot \Phi}$

        & $0.001$ & $0.1$
        \\ \hline
    \end{tabular}

\end{table}

\begin{figure}
    \centering
    \includegraphics[width=\columnwidth]{Figures/FW_Plots/flightPath.pdf}
    \caption{Trajectory-following response of the fixed-wing aircraft with the fixed-gain and the adaptive autopilot for various values of $\alpha_{\rm d}.$

    }
    \label{fig:flightPathFW}
\end{figure}

\begin{figure}
    \centering
    \includegraphics[width=\columnwidth]{Figures/FW_Plots/thetaPlot.pdf}
    \caption{Adaptive autopilot gains adapted by the RCAC algorithm for various values of $\alpha_{\rm d}$.
    Note that as the fixed-gain controller is detuned, RCAC compensates by providing larger values of gains.

    In the case where $\alpha_{\rm d}=1,$ RCAC gains are small, whereas, for $\alpha_{\rm d}<1,$ RCAC gains are larger.
    }
    \label{fig:thetaPlot}
\end{figure}

In order to quantify and compare the performance of the {adaptive
autopilot} with the {fixed-gain autopilot}, bank, elevation and trajectory-tracking error metrics are defined as
\begin{align}
    J_{\Phi} &\stackrel{\triangle}{=} \sqrt{\frac{1}{N} \sum_{i=1}^N (\Phi_{{{\rm s}},i} - \Phi_{{{\rm m}},i})^2}, \label{eq:cost_bank} \\
    J_{\Theta} &\stackrel{\triangle}{=} \sqrt{\frac{1}{N} \sum_{i=1}^N (\Theta_{{{\rm s}},i} - \Theta_{{{\rm m}},i})^2},\label{eq:cost_elevation} \\
    J_{\rm traj} &\stackrel{\triangle}{=} \sqrt{\frac{1}{N} \sum_{i=1}^N e_{{\rm x-track},i}^2},\label{eq:cost_xtrack}
\end{align}
where
$N$ is the number of measurements during the flight,
$e_{{\rm x-track}}$ is the cross-track error, defined as the minimum distance between the current position and desired trajectory.
Note that these error metrics are computed after each flight test.
Figure \ref{fig:RollCost} shows the error metrics for various values of $\alpha_{\rm d}$ with both the fixed-gain and the adaptive autopilot.

\begin{figure}[b]
\vspace{-0.5em}
    \centering
    \includegraphics[width=\columnwidth]{Figures/FW_Plots/allCostBar.pdf}
    \caption{Bank, Elevation, and trajectory-tracking error metrics obtained with the fixed-gain and the adaptive autopilots for different values of $\alpha_{\rm d}.$
    Note that all of the error metrics are scaled by the benchmark error metric, where the benchmark flight is obtained by setting $\alpha_{\rm d}=1$ and switching off the adaptive autopilot.
    }
    \label{fig:RollCost}
\end{figure}

Next, the case of actuator failure is considered.
In particular, the left aileron is assumed to be stuck at an unknown angular position.
Figure \ref{fig:stuck_actuator} shows the actuator failure scenario.
\begin{figure}
    \centering
    \includegraphics[width=\columnwidth]{Figures/stuck_actuator.png}
    \caption{Actuator failure scenario. The left aileron is stuck at an unknown angular position.
    }
    \label{fig:stuck_actuator}
\end{figure}

\begin{figure}
    \centering
    \includegraphics[width=\columnwidth]{Figures/FW_Plots/FixedAileron_Plots/flightPath.pdf}
    \caption{Trajectory-following response of the fixed-wing aircraft with frozen left aileron.
    }
    \label{fig:flightPathFW_stuck_actuator}
    \vspace{-1em}
\end{figure}

The aircraft is first commanded to follow a trajectory with the fixed-gain autopilot without any actuator failure.
This flight is considered to be the benchmark performance.
Next, the left aileron is then frozen at an unknown angular position, and the aircraft is commanded to follow the same trajectory with the fixed-gain autopilot.
In this case, as expected, the trajectory-tracking error increases.
Finally, with the left aileron is frozen, the aircraft is commanded to follow the same trajectory with the adaptive autopilot.
Figure \ref{fig:flightPathFW_stuck_actuator} shows the trajectory-following response in the three cases.
Note that the adaptive autopilot improves the trajectory-tracking error in the case of the stuck actuator and recovers the benchmark performance.
Figure \ref{fig:thetaPlot_stuck_actuator} shows the gains adapted by RCAC and Figure \ref{fig:RollCost_stuck_actuator} shows the error metrics in the case of the stuck actuator.

\begin{figure}
    \centering
    \includegraphics[width=\columnwidth]{Figures/FW_Plots/FixedAileron_Plots/thetaPlot.pdf}
    \caption{Adaptive autopilot gains adapted by the RCAC algorithm in the case of frozen aileron.

    Note that the dashed traces show the adaptive autopilot gains given by the RCAC algorithm in the nominal case, that is, with the operative aileron.

    }
    \label{fig:thetaPlot_stuck_actuator}
\end{figure}

\begin{figure}
    \centering
    \includegraphics[width=\columnwidth]{Figures/FW_Plots/FixedAileron_Plots/allCostBar.pdf}
    \caption{Bank, Elevation, and trajectory-tracking error metrics obtained with the fixed-gain and the adaptive autopilots for the actuator failure scenario.
    Note that the error metrics are scaled by the benchmark error metric, where the benchmark flight is obtained with the operative aileron and without the adaptive autopilot.
    }
    \label{fig:RollCost_stuck_actuator}
\end{figure}

\section{Conclusions and Future Work}
\label{sec:conclusions}

This paper presented an adaptive digital autopilot that can improve an initial poor choice of controller gains in a fixed-gain autopilot, and learn the autopilot gains without any prior knowledge of the dynamics .
The adaptive autopilot is constructed by augmenting the fixed-gain controllers in an autopilot with adaptive controllers.
The adaptive autopilot was used to fly a fixed-wing aircraft model in the Gazebo simulator.
The adaptive autopilot recovered the performance in the case where the fixed-gain autopilot was degraded and learned a set of gains in the case where the fixed-gain autopilot was completely switched off.
Furthermore, the adaptive autopilot improved the trajectory-tracking performance in the case where the aileron was stuck at an unknown angular position.
Future work will focus on experimental investigation of the adaptive autopilot in order to assess the performance of the adaptive autopilot under sudden changes, such as stuck actuators, chipped wing, and changes in environmental conditions.

 \bibliographystyle{IEEEtran}

redpajama_set_name: RedPajamaArXiv


text:
New plans to transform care for Derbyshire people with learning difficulties
A NEW plan to transform the way people with learning disabilities and autism are cared for and supported has been announced by Derbyshire County Council.
Sunday, 3rd February 2013, 12:00 pm
Updated Wednesday, 6th February 2013, 8:29 am
The county council is to work with local NHS partners to develop the plan which will see the development of `extra care' housing schemes and specialist residential care centres across the county, purpose-built for people with learning disabilities and autism.
The plan, which will be called the `Accommodation, Care and Support Strategy for people with Learning Disabilities', is the county council's response to the Department of Health's recent call for changes to the way people with learning disabilities are cared for following the Winterbourne View Hospital case.
Winterbourne View, a private hospital near Bristol, made national headlines when an undercover BBC Panorama investigation exposed neglect and abuse of patients with learning disabilities by staff.
The investigation led to four support workers and two nurses being jailed for between six months and two years for their part in the abuse, while five others were given suspended prison sentences.
The case resulted in the Department of Health issuing a number of recommendations for change to organisations providing social care and health, including local authorities.
One of the main recommendations is to reduce the number of people with learning disabilities living in hospitals and to end all `inappropriate placements' by 2014.
Other recommendations include stronger accountability and corporate responsibility for owners and directors of private hospitals and care homes and tighter inspection and regulation of hospitals and care homes for vulnerable groups.
New guidance on staff training will also be issued and there will be closer working between the NHS and local authorities providing social care.
The recommendations were considered by the Derbyshire Adult Care Board, made up of representatives from the county council's adult care and children's services, district and borough councils, Derbyshire Police, NHS, local GPs, the probation service and children's and adults safeguarding boards.
The Adult Care Board will now set up a project group to ensure the Department of Health recommendations are addressed and to develop the new Accommodation, Care and Support Strategy for people with learning disabilities and autism this year. The new plan aims to provide specialist short and long-term care for people with learning disabilities and autism, developing purpose-built apartments and centres, close to where people live.
Derbyshire County Council Cabinet Member for Adult Care Councillor Charles Jones said: "We are pleased to announce our plans to transform the way people with learning disabilities and autism are cared for and will be developing this over the months to come.
"It is very important we get this right and that we meet the recommendations set down by the Department of Health. The plan will make a real difference to the lives of people with learning disabilities and autism in the county in the future."
Further details will be announced later this year.
The county council's current £200 million investment plans to transform accommodation, care and support for older people, building up to 1,600 extra care apartments and four specialist community care centres, will be used as a template for the new programme.
The Board's proposal was supported by Derbyshire's Health and Wellbeing Board at its recent meeting.


The week-long Interpack Processes and Packaging trade fair in Germany concluded on May 14 with a visitor count that topped 175,000 from 120 countries. Show-goers had plenty to see and do, as approximately 2,700 exhibitors displayed cutting-edge packaging systems and food processing technology in 19 halls at the sold-out Düsseldorf Exhibition Center.
More than 175,000 visitors from 120 countries filled 19 halls at Interpack looking for innovative new packaging and processing systems. They were not disappointed. The dominating themes at the fair were resource efficiency for equipment and machinery, as well as for packaging material usage, quality and safety to guarantee highly desirable and counterfeit-proof finished products – especially in such sensitive segments as food and beverage – as well as diversity and flexibility for an ever wider range and shorter product cycles. This was abundantly evident in the particularly high number of innovations presented by exhibiting companies.
With foreign visitor participation of 66%, and some 75% of the exhibitors hailing from outside of Germany, Interpack 2014 not only set a new record for itself, but also scored a top rating across all Messe Düsseldorf trade fairs.
As always, equipment suppliers to the frozen food industry were in high profile. Members of the FrozenFoodsBiz.com editorial team checked out many of them. A review of some of what they found follows.
Thermoform packaging was in fine form at the Interpack Process and Packaging exhibition.
Varel, Germany-based Heinen Freezing GmbH & Co. Kg. managed to be at two places at one time on May 8, as representatives of the Kahl Group team exhibited at both the Interpack and the Seafood Processing Global in Brussels on that busy day. But from the 9th-14th the company's full concentration was on opportunities at the bustling Düsseldorf venue.
Cleaning nozzles above the belt maximize hygienic conditions in Heinen's Arctic spiral freezers.In Belgium it could be said that the emphasis was "mini,"as Heinen showcased its smallest cooling and freezing compact system. The unit is pre-mounted fully assembled on a base frame and able to industrially freeze seafood and other products at throughputs of up to 800 kilograms per hour.
At Interpack, on the other hand, the company spotlighted its "maxi" capacity Arctic spiral system for cooling and freezing food products. The stainless steel belted freezer was not produced only to appear at the show, as it was delivered directly to a client's baked goods factory after the fair's conclusion.
All Heinen spiral systems are of robust design for industrial multi-shift applications, explained marketing and sales support specialist Michaela Teschner. They feature high-quality machine components, and a minimum number of moving parts assure the highest degree of reliability.
Hygienic conditions are enhanced by lining wall and ceiling panels of the insulated enclosure with stainless steel. Optionally equipped with a facile belt-cleaning unit with pump for increasing pressure-generated foam, the system can be upgraded with an extended system that cleans the entire interior in addition to the belt and conveyor.
At the end of a production shift defrosting can be carried out manually, using hot gas or electrical heating mediums. Heinen has developed a special snow blow-off system that can extend production time before defrosting is necessary. In fact, the continuously working sequential defrosting operation allows for up to 144 hours of uptime without interruption.
Heinen also produces systems for proofing, pasteurizing and storing foods. With a product portfolio of five different spiral freezers, two fluidized bed freezing models and a multistage buffer freezer system, the company offers versatile designs for different applications. Between 40 and 50 units are built on an annual basis.
In recent years the Varel factory has been especially busy filling orders placed by manufacturers in the booming baked goods sector. At the same time, the machine builder's Arctic model has been popular with processors of fish, poultry, red meat and pizza products, while the Packfrost unit is in steady demand among makers of ice cream.
The company also provides complete, turnkey production line installation services in cooperation other equipment producers. With over 30 years of experience in installing systems at more than 500 plants around the world, Heinen engineers and support staff are proud that customers refer to them as "the freezing people."
The international dynamism of Hayward, California-headquartered Heat and Control was in high gear at Interpack, where the company's well versed crew of food processing systems experts from around the world offered advice and engaged visitors in conversation ranging from the "good vibrations" of FastBack horizontal motion conveyors to Spray Dynamics food seasoning and coating equipment, to frying and cooking systems for prepared foods, smaller footprint vacuum frying, new micro breaders, smart handling of shrimp in the production of IQF ready meals and other hot topics.
Heat and Control builds french fry and formed potato product fryer systems capable of handling up to 22.6 metric tons per hour. Additionally, it supplies complete lines including potato coating applicators, conveyors, weighers, inspection and packaging equipment.
In business since 1950, the company's offices and production plants span the planet from the USA and Mexico to Australia, New Zealand, China, Singapore, India, Scotland, South Africa and Holland. Among its global partners are Ishida (weighing, packaging, labeling and inspection systems), CEIA (metal detectors) and Urschel (food cutting technology).
Stramproy, Holland-headquartered Case Packing Systems (CPS) was on the scene with a high capacity CLP Casepacker, built to automatically load products into crates, cases or trays. Its in-feed system is capable of rotating individual products, allowing for a wide variety of packed patterns.
The CLP Casepacker for loading crates, cases and trays attracted a lot of visitors to the CPS stand during all seven days of the fair.When FrozenFoodsBiz visited the busy stand, Henri Veltmans, export manager, was thoroughly engaged in showing a the "ins and outs" of the versatile system to a group of potential clients gathered around the CLP Casepacker. Pieter Aquarius, managing director, was topside of the two-tier stand meeting with key customers.
Joan Berkvens, sales coordinator, welcomed the editors and explained that packed products conveyed through the system are first divided into a formation creating correct packing patterns to properly and efficiently fill carriers. Thereafter, a complete layer formation moves down the line to the retract conveyor, where side compacting takes place before pick up. Next, the retract conveyor withdraws and the layer of products is placed vertically into the product carrier.
CPS is enjoying good demand for the CLP model. In fact, the unit on active duty at the Interpack was destined to be shipped to a major frozen potato processing company in the USA right after the show.
In business since 1988, CPS focuses fully on automatic case packing systems with special emphasis on flexible packages and trays. Its machines pack products more compactly than is possible by hand, and therefore achieve substantial cost savings for users.
A visit to the BluePrint Automation BV (BPA) stand revealed a much larger company profile that existed during the last edition of Interpack three years ago. Since then expansion and acquisition, along with steadily rising international sales, have been major factors in the growth of the Woerden, Holland-based designer and builder of erecting machines for cartons and folded boxes, pick-and-place robots, turnkey packaging systems, wrap-around and cartoning solutions.
President Paul van der Meulen gave FrozenFoodsBiz a demonstration of the Universal Delta Robot in action. The new, modular vision guided system was developed for horizontal packing of stand up pouches, stick packs, four-side sealed pouches, sachets and pillow bags. The basic machine has two modules and packs up to 300 units per minute. It is expandable with extra modules to boost capacity, as needed.
Last year BPA acquired Culemborg, Holland-based Racupack, an established specialist in wrap-around and cartoning systems. Its Catamaran CPIII machine, on display in Düsseldorf, is designed to automatically erect, fill and close wrap-around cases, trays (lids) and RSC cases at a clip of 30 boxes per minute.
In the frozen food sector, the president reported that the ice cream market "has become more important for us." Indeed, BPA has earned "preferred supplier" status with a major multinational producer of frozen confectionery.
Van der Meulen, who has many years of experience in the China market, plans to devote more time to further develop prospects in the PRC. BluePrint Automation, which has an office in Hangzhou, aims to assemble equipment in China for sale domestically as well as elsewhere in East Asia.
Meanwhile, an increase in business and orders for multi-robot lines has prompted BPA's BluePrint Robotics division in the USA to add 18,000 square feet of workspace at a facility Longmont, Colorado. The company's vision-guided robotics systems are designed for sophisticated picking of individual packaged and unpackaged items for loading into containers, wrappers or Horizontal Form Fill and Seal (HFFS) machines.
Friedbert Klefenz, president of Bosch Packaging Technology, expressed satisfaction with the quantity and quality of visitors who stopped by the Stuttgart, Germany-headquartered company's stand.
At a press conference on the day the show kicked off, Klefenz reported that the company's sales grew by 22% in 2013 as revenues hit 1.1 billion euros – up by 200 million euros over the previous year's performance. Well over 90% of the turnover was generated in the pharmaceutical and food sectors (52% and 46%, respectively).
Europe, by far, is Bosch's biggest market, accounting for nearly 40% of sales in 2013. The Americas ranked second with a 27% share. North America was first in terms of regional growth, registering a 12% increase in turnover.
Among products aimed at developing markets is Bosch's entry-level SVI 2600 Vertical Form, Fill and Seal (VFFS) machine. Initially designed for small- and medium-size producers seeking to automate their packaging processes, it is also a cost-effective option for large manufacturers seeking to test market new products or fulfill low-volume requirements.
The equipment incorporates the same proven technology employed on higher-end baggers, such as servo-driven cross-sealing units, vacuum belts and Bosch/Beckhoff controls. The intermittent motion pillow, side gusseted and block-bottom bagger operates at 120 bags per minute.
Wolfertschwenden, Germany-headquartered Multivac utilized the Interpack venue to roll out its new R 085 entry-level thermoformer, which may be used for running both flexible and rigid films. It is aimed at small- and medium-size companies keen on entering the realm of automated thermoforming packaging for the first time.
The machine can be ordered with four standard format layouts, and can be used to produce packs with inert gas as well as vacuum packs. With a thermoforming depth of up to 80mm, the R 085 provides a wide range of pack design possibilities.
The system is equipped with the IPC 06 machine control as well as the HMI 2.0 user interface with a 12.1 touch screen. It also has a quick-change feature for forming and sealing dies with proven slide-in technology, which is integrated as standard in the die design. This makes it easier to convert the machine to other formats.
Sittingbourne, Kent, England-based Wire Belt unveiled the newly patented Vera-Link conveyor belt at the show, presenting it as one of the most durable open metal belts available for light- to medium-duty applications in the food processing industry.
Designed with Advanced Link Rod technology, the linking rods splice in as little as 30 seconds. There are no special tools or welding required, and the rods connect in the center, leaving no weak points. A lightweight alternative to heavy flat-wire belts, Versa-Link's spacing pattern offers product support to the edge of the belt, providing strength and long belt life.
The belt design is positioned as well suited for a wide variety of applications such as breading, battering, cooling, coating and frying. Made with quality stainless steel, it is able to operate in the most demanding conditions, and is easy to clean.
The company's Forged Edge technology eliminates catch points and sharp edges. The forged edges will not beak, snag or snap off during production, keeping lines running safely and efficiently. Versa-Link is said to offer one of the tightest transfers available, and can be easily retrofitted on existing equipment.
Oldham, Lancashire, England-based Loma Systems and Lock Inspection Systems showcased SureTune IQ3+ ST next generation metal detectors at the fair. Ideally suited for high-speed food manufacturing, they address drifting on the head coil and false rejects caused by subtle variations in atmospheric temperature and product characteristics. An intelligent validation system memorizes defined rest intervals by product and the individual retailer's code of practice.
Lock's improved Insight system has enhanced stability, height adjustability and a robust clamping sleeve that removes the need for resin assembly. For ease of installation, there are 200 product presets and a permanent memory store for up to 8,000 data events.
Giessen, Germany-headquartered Mettler-Toldeo Garvens launched the C3000 System at Interpack. Described as "a new generation of checkweighers," it covers a weighing range of up to 10 kilograms and allows food manufacturers to inspect as many as 600 products per minute.
The increased stability of the C3000 System provides protection against vibrations caused by other production line machinery and is said to offer enhanced throughput performance of up to 33%, with higher weighing accuracy. Its modular design allows for a variety of configurations, and manufacturers can choose from a range of optional product inspection technology combinations such as metal detection (CM Model), x-ray inspection (CX model) or vision inspection (CV model).
The flexibility of the technology allows processing lines to run at optimal speeds, inspecting a variety of products at correct frequency levels to ensure the best level of sensitivity is reached. Metal detection sensitivity options incorporate two tuned frequency ranges respectively, 100/300/800 Hz and 25/100/300 Hz, for optimum capabilities. A single Human Machine Interface (HMI) seamlessly controls the checkweighing and metal detection technology, enhancing overall equipment effectiveness by reducing programming time and the risk of operational error.
The systems also integrate centralized inventory management technology, enabling faster, more efficient reporting on product changeovers and the rejection of defective products.
Esslingen am Neckar, Germany-based Festo AG's valve terminal concept CPX/MPA has enabled the Milano, Italy-headquartered Cama Group to pave the way for a completely new machine generation, the results of which were on display for all to see at Interpack.
An example of the Festo-Cama collaboration for new "Breakthrough Generation Machines" is this "CL" cartoner. Operating on a side-loading principle, it takes up significantly less space on the factory floor. In three steps, cartons are opened, filled with many different kinds of products, and then closed.This new series of machines highlights Cama's renowned lean design of secondary packaging equipment and robots. "This machine generation will create entirely new opportunities for growth for us," predicted Rini.
One characteristic feature of conventional machines is the large control cabinet outside the main structure. The controllers within the cabinet are connected to drives, sensors and valves by a multiplicity of cables and lengths of tubing several meters long.
With the Breakthrough Generation, Cama completely restyled its machines. This allows machine footprint reduction by integrating the control cabinets with electrical and pneumatic components into the machine pedestal's angles. Such a compact design helps to minimize cabling and makes it easier to place utility devices right where they are needed, and thus make them more easily accessible.
"Significantly fewer and shorter cables and tubes to be connected simplify and shorten installation. This is a further distinguishing feature," explained the machine builder as he described the gain in efficiency.
"What is more, the CPX offers diagnostic functions. This makes it easy for us to meet the demands of large branded-product manufacturers, for example for preventive maintenance," continued Rini.
Attention has also been paid to machine safety. The Festo soft-start and exhaust valve MS6-SV is used to exhaust the system. It provides reliable protection against unexpected start-up and has an exhaust capacity 1.5 times its pressurization capacity.
Cama has also introduced the CL 175, an extremely flexible side-loading cartoning machine. It has been completely redesigned, both in layout and functionality. The equipment can load flow-wraps, pouches, bags, thermoformed trays, blister packs and more into pre-glued cartons.
The side-loading unit loads products into cartons with an intermittent-continuous motion. This handling unit consists mainly of a Festo electric axis EGC for a precise approach to intermediate positions and a pneumatic mini slide DGSL. EGC helped to reduce the mounting time by 30% compared to the previous self-made electrical axis. The use of both pneumatic and electrical drive technologies allows high precision to be obtained together with a high load capacity.
Next, the cartons move toward the final closure station. It can work in continuous or intermittent mode. Finally, the cartons get onto the outfeed conveyor.
The SD-97W automatic encrusting and forming machine from New Taipei City, Taiwan-headquartered Anko Food Machine Co., Ltd. attracted plenty of attention at the show. The system uses a shutter mold to form two colors or a solid color casing, dough-based shell or pastry to be stuffed with filling. This is accomplished by simply changing the forming mold and filling facilities, such as meat bun, coxinha, mammoul, meat pie, kubba, potato bread, rice cake, mochi, marzipan, croquette, crystal dumpling, moon cake, filled focaccia bread and cylindrically shaped products.
Taiwan's Anko Food Machine Co., Ltd. impressed show-goes with its SD-97W model automatic encrusting and forming equipment.Fillings can range from bean or peanut paste to powder, minced meat, or sesame paste, as well as whole peanut pieces, macadamia, pistachio or other kinds of nuts, bird egg, or small fruits and berries.
Five programmable memories may be utilized, as well as various synchronized functions. Dough and filling volume may be increased simultaneously, and conveyor speeds can be timer-controlled.
Headed up CEO Robert Ou-Young, the company was established in 1978, initially to exclusively produce automatic seed sprouters. It evolved over time, and today Anko offers a full range of high-tech food processing machinery including automatic spring roll, dumpling, ravioli, samosa, shiu mai, won ton, empanada and other kinds of ethnic food manufacturing equipment.


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Rapid response to the telephone complication a little tortuous of healthy advice from the technician.


Sheheryaar Munawar just got engaged in Karachi to a young woman named Hala Soomro. Hala is a doctor at a local hospital and the two recently had a private ceremony where they got engaged. Take a look at how cute this couple is.
Sheheryaar Munawar's upcoming film Parey Hat Love is set to release on Eid ul Azha. He will be paired opposite Maya Ali. Mahira Khan was set to appear in the film with him but Maya Ali has been cast for the lead role whereas Mahira will be appearing in a short role in the film.
Now that's a thorough gentleman and a keeper!
He attended the Masala Awards and was given the Most Versatile Actor award at the Masala! Awards 2018 held in Dubai at Madinat Jumeirah. The Masala! Awards featured the best and the most coveted actors and performers of the season. The Masala! Awards 2018 had Faraz Manan and Kareena Kapoor Khan showcasing Faraz Manan's latest collection. The show was also attended by Kartik Aaryan with whom Sheheryaar also posed later.
Sheheryaar appeared in Ho Mann Jahan alongside Mahira Khan as well. In this film he played an angry young man who wanted to pursue singing but barely had the discipline for it. He later appeared in Saat Din Mohabbat In with Mahira Khan again which received mixed reviews. Sheheryaar will also appear opposite Syra Shahroz in the upcoming action thriller Project Ghazi which is set to release in March 2019.
Mahira Khan's '7 Din Mohabbat In' Teaser is OUT and it's a Laugh Riot!


text:
Cleveland Cavaliers continue impressive road trip with victory over Spurs behind Darius Garland, Jarrett Allen
Cavaliers center Jarrett Allen (31) shoots over San Antonio Spurs center Jakob Poeltl (25) during the first half of the Cavs' 114-109 win Friday night in San Antonio. [Eric Gay/Associated Press]
SAN ANTONIO — Darius Garland scored 32 points and the Cavaliers beat San Antonio 114-109 on Friday night, extending the Spurs' losing streak to five.
The Cavs held the Spurs scoreless for five minutes starting with 6:05 remaining in the fourth and outscored the Spurs 30-23 in the quarter.
"We knew we had to most importantly get stops. That was the main thing," Garland said. "If we got stops, we knew that we were going to at least get a good shot up or score. As long as we got the stops down the stretch, we felt confident in our offense."
Guard Darius Garland (10) scored 32 points to lead the Cavaliers to a 114-109 win over the San Antonio Spurs on Friday night. [Eric Gay/Associated Press]
Jarrett Allen finished with 17 points and 16 rebounds for the Cavs, who won their third in a row and fourth in five games.
Dejounte Murray had 30 points, 14 rebounds and eight assists for the Spurs, who are 1-7 in the new year. Keldon Johnson added 18 points and Bryn Forbes had 15.
The Spurs struggled against the Cavs' frontcourt of 7-footers Evan Mobley and Lauri Markkanen, and the 6-11 Allen.
Mobley added 15 points and Markkanen had eight.
The trio also helped stymie Spurs center Jakob Poeltl, who was scoreless on just four field goal attempts and no free throws.
The Cavs shot 53% from the field in the first half, with two alley-oop dunks to Mobley and Allen. The Cavaliers finished with four alley-oop dunks. Allen threw down the final one with 1:53 remaining to give the Cavs a 108-103 lead seconds after Markkanen stuffed a one-handed dunk over Poeltl.
"There is a connectedness in our group where they talk to one another, they hold each other accountable," Cavs coach J.B. Bickerstaff said. "They have a collective spirit to want to get it done. When you have that, there is no fracturing, there is no separation. Everybody comes together and they go out and compete and try to get the job done. I thought they did a great job of that."
Cavaliers coach J.B. Bickerstaff argues a call during the second half of a 114-109 win over the San Antonio Spurs on Friday night. [Eric Gay/Associated Press]
The Cavaliers had a 20-point advantage in scoring 60 points in the paint. The Spurs attempted to keep pace by going 15 for 34 on 3-pointers but couldn't maintain a lead in the third quarter.
"They are trying their best, we've just got to do it better," Spurs coach Gregg Popovich said. "We've got to have fewer turnovers. We've got to have better block outs and not give up as many offensive boards. Good decisions on shots, finding the 3-man better.
"There are lots of things we can improve, but we have to be patient to some degree because the combinations that we have, they have basically never played together and some of them are quite young. That's going to take some time. They're taking their lumps now, but Cleveland is a hell of a team."
The Spurs were on a 15-6 run in the final 5½ minutes of the third quarter to take their largest lead before Cedi Osman drained a 3-pointer at the buzzer to pull the Cavs within 86-84.
"Those hurt," Allen said. "Those hurt a lot more than it shows on the scoreboard. It's just deflating. You go on a big run like they did and then here I'm pretty sure Evan made the pass to Cedi and it was a swish. You could feel the crowd was deflated. You saw the Spurs just walking off to the bench. It's tough when you have that momentum and it's just shut down like that."
Cavaliers: Point guard Rajon Rondo missed his second consecutive game with a sore right hamstring. Coach J.B. Bickerstaff did not have an update on Rondo's return. … Isaac Okoro had six points in 16 minutes in his return after missing five games due to a sprained left elbow. … The Cavs are 14-9 on the road after going 9-27 last season. … Kevin Love had seven points and four rebounds in 16 minutes. He entered the game averaging 18.7 points and 7.6 rebounds in his previous 10 games.
Spurs: Derrick White and Tre Jones remain in the league's health and safety protocols due to COVID-19. Coach Gregg Popovich said he does not know when either will return. … Murray leads the Spurs in points, assists and steals, and is second in rebounding. He entered the game averaging 18.8 points, 8.2 rebounds, 8.9 assists and 2.1 steals. … Drew Eubanks missed the game with an unspecified illness, which was not COVID-19. Eubanks was in uniform, sitting with the team on the bench.
This article originally appeared on Akron Beacon Journal: Darius Garland, Jarrett Allen lead the Cavs past the Spurs
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Matcha has hit the restaurant and social media scene and become the hottest food trend and possibly most instragrammable food ingredient since 2015 and it seems like this matcha madness is never dying.
While matcha ice cream can be seen everywhere in Australia, Movenpick decided to take on a different direction, gave the matcha craze a twist, and created this hand-baked MATCHA WAFFLE CONE.
Collaborating with Vanilla Zulu's Executive Chef and acclaimed Author, Mel Townsend, Movenpick brought us the perfect waffle cone that pairs beautifully with the 24 Movenpick ice cream flavours.
Erica and I were so excited when we first heard about the matcha waffle cone exclusive tasting! And we were not disappointed! Their ice cream were luscious as per usual, living up to their name. The matcha waffle cone was more on the subtle side of (but not without) flavour, making it an ideal match for the Movenpick ice cream. As for those who prefer a stronger matcha flavour, you can always choose something lighter out of the 24 ice cream flavours they have in store!
Erica and I also got to experience rolling our own matcha waffle cones!! I have to say, it was not an easy task to roll out a perfectly green and well-shaped cone! We really appreciate the effort the Movenpick staff put into hand-baking every single waffle cone!


Adaptive learning resource systems, fully functioning at the region and division levels, effectively developing and distributing adequate and varied learning resources to teachers and learners from both the formal basic education and ALS systems.
Improvement of instructional and learning materials system through support for the assessment, acquisition, adaptation, development, production and distribution of teaching/learning materials to schools.
Digitized available student learning materials (including from PASMEP, PROBE, PRODED, BEAM, TEEP, SEDIP, etc), particularly for reading in the early grades and TLE programs, English, Science and Mathematics in other grades, ADM and ALS.
Enhanced provisions of quality instructional and learning materials, particularly in reading in early grades and TLE, English, Science and Mathematics in other grades.
Alternative Delivery Modes and Learning Systems.
Improved development and utilisation of Quality Assurance (including Monitoring and Evaluation) systems for provision and utilisation of learning resources.


More pics from NYC (New York City.) I've been playing around the light-room and using some of the fun presets.
The expressions on their faces are so funny! We had been traveling around cold NYC all day and saw a show and it was about 11PM on the subway.
Hi Carly, these are great creations, though I am a newbie on PS. I have heard of light room but not very familiar with it.
P.S. I think you put in the wrong link on Outdoor Wednesday. Please check it out. Thanks.
Who doesn't love Mary Poppins. HaHa! Live the sepia toned photo as well!
Lightroom 2 looks like it's a lot of fun. It's magical just like MAry Poppins!
It looks like it was a little chilly there in New York. So how long did you stay? What a great place to visit. I would love to go there one day.
I love the first two shots. I like the way that you played with the lighting, very neat!
And the Mary Poppins was just priceless!
Yo! You takin' my picture lady? Nice shot Carly. Subways are a great place to observe and photograph people. Works well in sepia.
Those expressions are priceless lol! They look stunned but interested.
Love your Sepia picture! Also your WWed - well more is there to say, this lady is a lady!!!???
Great photos of the Big Apple. I agree the expressions of the subway riders are funny and interesting.
Mary Poppins always makes me smile.


Brazilian midfielder Fred has arrived at Manchester United's training ground for a medical ahead of his pending transfer to the club.
The Shakhtar Donetsk star is expected to complete a deal worth around £52.5 million ($70m) in the next 24 hours, with his current club's president Rinat Akhmetov having insisted it would take a club-record sale for him to leave the Ukrainian outfit .
And Fred was spotted arriving at United's training facility early on Monday morning ahead of his medical, after which he is likely to pen a four-year deal with a club option for a fifth term.
The 25-year-old came on as a substitute in Brazil's win over Croatia in a friendly at Liverpool's home, Anfield, on Sunday and later caused a stir by tweeting his congratulations to his team-mates with a location tag of Manchester.
His appearance on Sunday was his eighth for the Selecao, and he has been included in head coach Tite's final 23-man squad for this summer's World Cup finals.
The midfielder has spent the last five years with Shakhtar having begun his senior career with Internacional in his homeland. He had previously been a target of Manchester City, but Pep Guardiola's side withdrew their interest in January.
Fred looks set to become United's first signing of the summer, with Jose Mourinho also primed to snap up Porto full-back Diogo Dalot in the coming days .
Mourinho sparked rumours of a move for Fred as far back as April when insisting that "a team without a Brazilian is not a team" .


The exhibiting companies included hundreds of established and emerging beverage brands.
Although food and beverage manufacturers continue to develop products that support healthy, better-for-you solutions, indulgent offerings still remain a key component to consumers' consumption habits.
When it comes to grocery retailing, analysts are seeing how consumers' desire for better-for-you food and beverages have contributed to the growth of the natural and organic retail channel.
Keep it Simple Syrup (KISS) added a new flavor to its lineup, Sugar Cane KISS.
The sports drink market is facing stiff competition from other beverage categories and remains to be seen whether it will make its comeback victory.
The exhibiting companies included hundreds of beverage brands as well as suppliers for the beverage industry.
In Beverage Industry's New Product Development Outlook 2017 Study, respondents indicated which trends they think will be the most popular in 2018.
As more consumers take a back-to-nature approach to their health and nutrition, recognizable, plant-based botanical ingredients like green tea, guarana, turmeric, acai, vanilla and ginger are adding functionality, healthy hydration, natural caffeine and clean-label appeal to a variety of beverages.
Beneo, Morris Plains, N.J., announced that it will focus on healthier snacking at this year's IFT Annual Meeting & Food Expo, taking place June 25-28. The company will present natural, clean-label solutions that respond to consumer trends, including sugar replacement, healthy weight, digestive health and improved energy, the company says.


text:
I'll Be Back Insists Axed Boss Royle
Joe Royle claims he is not finished in management despite being sacked by Manchester City.
Royle's three-year reign as City boss came to an abrupt end yesterday morning when he was dismissed by chairman David Bernstein during a three-minute meeting.
Bernstein sacked Royle because he would not agree to sweeping changes to his backroom staff.
It is also understood that City were unhappy with the drinking culture at the club among some of the players.
Royle, 52, had planned to retire from management in three years' time at the end of his City contract when he would have been 55 and he feels he has got a couple of good years left in him yet.
Royle was due to fly to Spain today for a short holiday with some old footballing friends and he will consider his future when he returns.
"I will be having a short break then we will see," he said.
"I have said before that I would retire at 55, so I will have a holiday and then come back to two or three good years which are left in me yet.
"I don't feel as though I have anything to prove but I want to carry on working. I am proud of my record at City."
Royle, who guided the Blues from the Second Division to the Premiership in successive seasons, admitted he had been surprised at losing his job, but he claimed he parted from Bernstein on good terms.
"I must admit I came in this morning with the idea of making plans for next season but I sensed immediately that it wasn't to be," he said.
"It all ended amicably. It was a three-minute meeting, I shook his hand and left."
Bernstein claims he already has a provisional list of possible successors to Royle.
George Graham, Dave Bassett, Mick McCarthy and Steve McMahon have already been touted for the job and an appointment could be made as soon as next week.
Bernstein feels City are still an attractive proposition, despite being relegated from the Premiership.
"We believe this will be a much sought-after position," he said.
"I think the club now does have a reputation for being a well-run club. We've worked very hard at professionalising the place.
"We've got a strong board, a strong team of people at the club and we have a new stadium coming to us in two years' time, which is a magnificent 50,000 stadium."
Dwight GayleDwight Gayle could be ruled out until March as Steve Bruce admits 'huge disappointment'Newcastle United striker Dwight Gayle has suffered a season from hell
Allan Saint-MaximinSteve Bruce welcomes back Allan Saint-Maximin and Fabian Schar for Chelsea visitThe Magpies are aiming to hand a comeback to French ace at home to the Blues


text:
Viva La Civilization Revolution
by Gary Hodges
If only there was a little Slim Pickens riding it.
Gandhi is threatening to invade my country if I don't share the secrets of gunpowder with him. Consulting with my advisors, I'm told his army is no threat, their technology far behind mine. I don't believe the numbskulls whispering in my ear: the Indian's army has marched right to the edge of my capital for maximum bargaining leverage, and outnumbers mine 6 to 1. I hand over our people's knowledge of gunpowder, and the formerly raging little wise man's face softens. He thanks me casually as if we weren't just on the brink of war, and then marches his army back to India as if nothing ever happened.
He may think it's over, but I won't forgive this humiliation so easily. I put in an order for what will ultimately be a fleet of tanks destined to roll on New Delhi sometime in the next decade. The voters won't go for it of course, so I'll just take a page from Emperor Palpatine and dissolve the Senate before seeking my revenge. A bunch of politicians aren't getting in the way of me making the Mahatma kneel at my feet.
No question: aside from the bizarre, quasi-historical spectacles you encounter in Civilization Revolution (President Genghis Khan launches his first battleship, anyone?), you sometimes get to see a new, ugly side of yourself, too. And it's damn fun.
For those tragically unfamiliar, Sid Meier's Civilization games – much like Will Wright's Sim titles – start with a simple concept: guide a civilization from its bearskin-wearing origins all the way to a modernity of atomic power, space flight, and assholes sitting alone in restaurants talking too loudly on a silly headset phone.
Should your people be enlightened, cultured artisans? Technological geniuses? What about savage, warmongering monsters every step of the way? All up to you. And as you spread out across the map growing around (or through) neighboring tribes, you even manage the day-to-day problems of a city planner: should you build a temple or a marketplace in your capital? Fortify the town with archers or form up an army of horsemen to ride out and, ahem, "visit" the locals? Each has ramifications.
However complicated this all sounds, the game does an excellent job of walking you through the system, even giving you a comprehensive in-game encyclopedia to refer to as needed. The basics are easy to pick up, and most games move briskly, short enough that you can squeeze in a couple before bedtime.
If anything, that's the aspect that will disappoint the devoted fans of the series: Revolution is a stripped, streamlined interpretation of past Civ games. On the bright side, fewer nuances mean the game clicks along much faster than its PC brethren, making a session less of a commitment and more accessible to novices. But to do this, reams of micromanagement got sacrificed on the altar of simplicity, making it a bummer for PC fans who actually enjoyed the minutiae of, say, picking the specific acres around a city to be irrigated.
Likewise, the game is a bit short on options – multiplayer is great, but forcing players to take on computer-controlled playmates is silly – and the computer's AI ranges from braindead on most difficulties to an abrupt mad-dog-insane on the highest two, with little in between. Likewise, it seems to have an unspoken agreement with other AI tribes: "gang up on the organic lifeform."
But then you pay Cleopatra to declare war on Napoleon, hoping the distraction will allow you a chance to finish your nuclear weapon… and all the little problems just don't seem like that big a deal.
More:Emperor PalpatineGame OnGenghis KhanMahatma GandhiNew DelhiTechnology