Adaptive compensation control for nonlinear stochastic multi-agent systems: An event-triggered mechanism

This paper proposes an adaptive compensation control algorithm for solving the actuator failures problem of nonlinear stochastic multi-agent systems (MASs) under the directed communication topology. It should be emphasized that the coexistence of unknown nonlinearities, stochastic perturbations and actuator failures makes the implementation of control protocol very difficult and extremely challenging. To achieve the control objective, fuzzy logic systems (FLSs) are first employed to deal with the unknown nonlinearities of each agent. Then, the threshold-based event-triggered mechanism is further considered to reduce the communication burden of the system in the case of limited communication resources. Moreover, the issue of "explosion of complexity" is solved by using dynamic surface control (DSC) technique in the process of backstepping design. With these efforts, the actuator failures are circumvented and the outputs of the followers converge to the convex hull spanned by the multiple leaders' outputs. Finally, the simulation results of multiple single-link robots show the validity of the proposed design scheme.