Adaptive Fuzzy Predefined-Time Control for Stochastic Nonlinear Systems Against Actuator and Sensor Faults

In this article, the practically predefined-time adaptive fuzzy tracking control problem for stochastic nonlinear systems, where the system under consideration includes actuator and sensor faults, is studied. Fuzzy approximation technology not only processes unknown nonlinear dynamics but also solves the problem of sensor fault. The introduction of the first-order filter simplifies the design process of the conventional backstepping controller. The stability time of the system can be adjusted according to the needs of the users, so the finite-time and fixed-time control results can be improved. Based on the fourth-order Lyapunov function, a novel practically predefined-time stochastic stabilization (PPSS) control framework is proposed. Based on the designed control scheme, the predefined-time stability of the controlled system is achieved. Finally, the illustrative examples validate the performance of the method presented.