Adaptive fuzzy control for induction motors stochastic nonlinear systems with input saturation based on command filtering

This paper presents a command-filter-based adaptive fuzzy control method to solve stochastic disturbances and input saturation problems for induction motors (IMs) drive systems. Firstly, the fuzzy logic systems (FLSs) are employed to cope with the stochastic nonlinear functions in IMs drive systems. Secondly, the quartic Lyapunov function is selected as the stochastic Lyapunov function and the adaptive backstepping method is used to design controllers. Then the command filtering technology is utilized to deal with the explosion of complexity in conventional backstepping, and the filtering error is eliminated by the designed compensating signal. Finally, the effectiveness and superiority of the proposed method are demonstrated by simulation results.