Fixed-time adaptive fault-tolerant control of stochastic nonlinear systems with time-varying full-state constrains

This paper investigates the fixed-time adaptive fault-tolerant control (FTC) problem of stochastic nonlinear systems with unknown virtual control coefficients (UVCCs) and time-varying full-state constraints (FSC). Firstly, the boundary estimation method and the neural networks (NNs) are introduced to deal with UVCCs and approximate unknown functions respectively. Then, two different types of parametric adaptive laws are constructed to satisfy the stochastic systems fixed-time stability theory and compensate the actuator fault. Furthermore, combining backstepping technique and time-varying barrier Lyapunov functions (BLFs), the designed controller can ensure that all closed-loop signs of the system are bounded in probability and the time-varying FSC are not violated. Finally, the effectiveness of the proposed control scheme is verified by two examples.