Distributed Adaptive Control With Adaptive Control Allocation for Multiagent Systems

Multiagent system performance is detrimentally affected by system uncertainties due to the presence of modeling errors, dynamical or external unknown effects, and unknown actuator degradation. Therefore, in this paper, a novel distributed adaptive controller with adaptive control allocation is proposed to compensate for these uncertainties in the networked high-order multiagent system that consists of over-actuated agents. A Lyapunov stability analysis is given to show asymptotic convergence of the tracking error between the closed-loop agent states and the reference model states. Simulation results on rotational dynamics of a networked multiple hexacopter system are provided to show the efficacy of the proposed distributed method.