Robust Adaptive Fault-Tolerant Tracking Control for Nonaffine Stochastic Nonlinear Systems With Full-State Constraints

In this article, the adaptive fault-tolerant tracking control problem of nonaffine stochastic nonlinear systems with actuator failures and full-state constraints is studied. To surmount the design difficulty from nonaffine nonlinear term with multi-input and single-output (MISO) faulty modes, a novel nonlinear fault compensation function with adjustable parameter factor is first introduced to establish a standard adaptive fault-tolerant control (AFTC) strategy based on the mean-value theorem. Then, the remaining nonlinear function, including the partial loss of effectiveness, outage, and stuck cases, together with the constructed compound nonlinear function can be approximated by using the suitable fuzzy-logic system (FLS). Moreover, it is shown that all the states of nonaffine stochastic nonlinear systems are not violating the preset constraint bounds by employing the barrier Lyapunov functions (BLFs). Also, the given adaptive controller can guarantee all the closed-loop signals are uniformly ultimately bounded (UUB) in probability in the sense of fourth-moment within the appropriate compact sets. Finally, two simulation examples are given to demonstrate the validity of the proposed method.