Adaptive fuzzy decentralized tracking fault-tolerant control for stochastic nonlinear large-scale systems with unmodeled dynamics

This paper studies the adaptive fuzzy decentralized tracking fault-tolerant control design problem for a class of unknown stochastic nonlinear strict-feedback systems with actuator faults. The stochastic systems under study have the characterizations of unknown functions, unmodeled dynamics and without the direct measurements of state variables. Fuzzy logic systems are employed to identify the unknown stochastic nonlinear systems, and a fuzzy state observer is established for estimating the immeasurable states. The dynamic surface control (DSC) design approach based on the backstepping technique is presented to design adaptive decentralized tracking fault-tolerant controller. It is proved that proposed control approach guarantees that all the variables of the closed-loop system are bounded in probability, and also that the tracking errors converge to an adjustable neighborhood of the origin regardless of actuator faults and unmodeled dynamics. The simulation results are provided to illustrate the effectiveness of the proposed control approach.