Data-driven fault-tolerant consensus control for nonlinear multi-agent systems under sensor and actuator faults

This paper investigates the consensus control problem for unknown nonlinear multi-agent systems (MASs) with both sensor and actuator faults. Different from the existing data-driven control methods for unknown nonlinear MASs without faults, a new data-driven adaptive fault-tolerant control (DDC-FTC) method is proposed. Firstly, the data mapping of agents with sensor and actuator faults is established by the locally dynamic linearisation technique. Then, by employing an adaptive fault compensation method, a fault-tolerant controller is designed for unknown nonlinear MASs. Especially, through the stability analysis, it is proven that the consensus tracking error under the designed controller is bounded, where the error bound is related with the parameters in the proposed compensation mechanism, which can be effectively decreased by tuning the parameters. Finally, simulations are given to verify the correctness of the proposed DDA-FTC approach.