Adaptive fuzzy fault‐tolerant control of stochastic nonlinear multiagent systems with input quantization and state constraints

Abstract

SummaryThis paper is dedicated to the problem of adaptive fuzzy fault‐tolerant control (FTC) for a class of stochastic nonstrict feedback nonlinear multi‐agent systems (MASs) with input quantization and full state constraints. Firstly, based on the backstepping technique and the bounded estimation method, the effect of actuator faults can be eliminated by the proposed adaptive updating laws. Secondly, the stochastic barrier Lyapunov functions (BLFs) are constructed to ensure that all state constraints are not violated. Meanwhile, the introduction of input quantization can effectively save network resources and reduce computational burden. It is further shown that all the closed‐loop signals are uniformly bounded, and the consensus tracking errors asymptotically tend to zero. The effectiveness of the proposed control scheme is illustrated by a numerical example.