Adaptive fault-tolerant containment control for stochastic nonlinear multi-agent systems with input saturation

This article considers the fault-tolerate containment control problem for stochastic nonlinear multi-agent systems in the presence of input saturation and sensor faults. In order to solve the problem of input saturation, a smooth function is used to approximate the controller saturation function. Due to the excellent approximation characteristic, neural network (NN) is used to deal with unknown nonlinear functions and unknown sensor faults. Meanwhile, by using the auxiliary system and combining adaptive backstepping technique with adaptive NN control, a fault-tolerant containment control approach is proposed. By using graph theory and stochastic Lyapunov stability theory, it can be proved that all signals in the closed-loop system are semi-globally uniformly ultimately bounded in probability. Finally, simulation results are given to show the effectiveness of the proposed control scheme.