Networked multiagent systems consist of interacting agents that locally exchange information, energy, or matter. Since they do not in general have a centralized entity to monitor the activity of each agent, resilient distributed control system design for networked multiagent systems is essential in providing high system performance, reliability, and operation in the presence of system uncertainties. An important class of such system uncertainties that can significantly deteriorate the achievable closed-loop system performance is sensor uncertainties, which can arise due to low sensor quality, sensor failure, sensor bias, or detrimental environmental conditions. This paper presents a novel distributed adaptive control architecture for networked multiagent systems to mitigate the effect of sensor uncertainties. Specifically, we consider agents having high-order, linear dynamics with agent interactions corrupted by unknown exogenous disturbances. We show that the proposed adaptive control architecture guarantees asymptotic stability of the closed-loop dynamical system when the exogenous disturbances are time-invariant and uniform ultimate boundedness when the exogenous disturbances are time-varying. A numerical example is provided to illustrate the efficacy of the proposed distributed adaptive control architecture.
['Ehsan Arabi', 'Tansel Yucelen', 'Wassim M. Haddad']
Mitigating the effects of sensor uncertainties in networked multiagent systems