Distributed robust fault-tolerant consensus tracking control for multi-agent systems with exogenous disturbances under switching topologies

In this article, the H-infinity consensus tracking problem for multi-agent systems (MASs) under switching communication topologies is studied. In the objective system, the unknown nonlinear function, exogenous disturbances, and actuator faults are considered. For this problem, a new fully distributed fault-tolerant control method is developed via utilizing adaptive mechanisms. A sufficient condition is obtained to guarantee the stability of the considered closed-loop system by topology-based average dwell time technique combined with Lyapunov stability theory. Unlike the traditional method to estimate the weight matrix, the neural network is used to estimate the norm of weight vectors. Thus, the difficulty that the unknown nonlinear function cannot be compensated when outage or stuck faults occur in some actuators is solved. Compared with the existing controllers for nonlinear MASs, the proposed controller does not require any knowledge about the terms relevant to the global information associated with the network. Furthermore, the proposed controller can compensate for the leader's unknown bounded input and actuator faults. Besides, the closed-loop system is proven to be stable by the developed controller, and all followers can track the state of the leader. Finally, a numerical simulation is given to validate the effectiveness of the proposed protocol.

Automated summary

This article studies the H-infinity consensus tracking problem for multi-agent systems under switching communication topologies and proposes a new fully distributed fault-tolerant control method utilizing adaptive mechanisms, using neural networks to estimate the norm of weight vectors and solving the difficulty of compensating for unknown nonlinear functions during actuator faults.