Adaptive fault tolerant cooperative control for hybrid nonlinear multiagent systems via switching functional

This paper investigates the fault tolerant cooperative control of strict-feedback hybrid multiagent systems with unknown nonlinear dynamics. The hybrid multiagent systems consist of both continuous-time and discrete-time agents, which suffer from potential multiple actuator faults. To deal with the sampled neighborhood information for continuous-time agents and to generate $n$-step prediction for discrete-time agents, hybrid distributed estimators are developed to estimate the state of the leader. To mitigate the impact by faulty actuators, a unified learning-based switching functional is introduced to select different sets of actuators automatically and locate the healthy set. By this means, the requirement for fault identification or fault detection and isolation mechanisms is relaxed. The controllers for continuous-time and discrete-time agents are designed separately for accommodating the difference between their dynamics. Through Lyapunov analysis, it is shown that the followers’ output can track the leader’s output and all the signals in the closed-loop are bounded. The numerical studies verify the effectiveness of the proposed scheme.