Finite-Time Adaptive Fuzzy Control for Stochastic Nonlinear Systems with Input Quantization and Actuator Faults

This study examines the problem of fuzzy adaptive finite-time control for strict-feedback stochastic nonlinear systems in the presence of actuator faults and quantization. The nonlinear functions inside the systems are approximated using fuzzy logic systems (FLS). Fuzzy approximation abilities are employed to develop an adaptive fuzzy finite-time controller based on the backstepping design methodology and the Lyapunov function approach. It is shown that, despite quantization and unknown actuator faults, the closed-loop system states stay bounded and the tracking error is confined to a small range close to equilibrium in finite time. The simulation examples are provided to illustrate the efficacy of the control strategy.