Introducing DAIMYO: a first-time-right dynamic design architecture and its application to tail-sitter UAS development
<|reference_start|>Introducing DAIMYO: a first-time-right dynamic design architecture and its application to tail-sitter UAS development: In recent years, there has been a notable evolution in various multidisciplinary design methodologies for dynamic systems. Among these approaches, a noteworthy concept is that of concurrent conceptual and control design or co-design. This approach involves the tuning of feedforward and/or feedback control strategies in conjunction with the conceptual design of the dynamic system. The primary aim is to discover integrated solutions that surpass those attainable through a disjointed or decoupled approach. This concurrent design paradigm exhibits particular promise in the context of hybrid unmanned aerial systems (UASs), such as tail-sitters, where the objectives of versatility (driven by control considerations) and efficiency (influenced by conceptual design) often present conflicting demands. Nevertheless, a persistent challenge lies in the potential disparity between the theoretical models that underpin the design process and the real-world operational environment, the so-called reality gap. Such disparities can lead to suboptimal performance when the designed system is deployed in reality. To address this issue, this paper introduces DAIMYO, a novel design architecture that incorporates a high-fidelity environment, which emulates real-world conditions, into the procedure in pursuit of a `first-time-right' design. The outcome of this innovative approach is a design procedure that yields versatile and efficient UAS designs capable of withstanding the challenges posed by the reality gap.<|reference_end|>
@article{wauters2024introducing,
    title={Introducing DAIMYO: a first-time-right dynamic design architecture and
  its application to tail-sitter UAS development},
    author={Jolan Wauters, Tom Lefebvre, Joris Degroote, Ivo Couckuyt, Guillaume
  Crevecoeur},
    journal={arXiv preprint arXiv:2409.09820},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.09820},
    primaryClass={math.OC cs.RO cs.SY eess.SY}
}