Adaptive fuzzy control for permanent magnet synchronous motors considering input saturation in electric vehicle stochastic drive systems

Abstract In this paper, an adaptive fuzzy control method based on command filtering is proposed for permanent magnet synchronous motors (PMSMs) stochastic nonlinear systems (SNSs) with input saturation in electric vehicle. The unknown stochastic nonlinear functions are approached by the fuzzy logic system (FLS). Then, the command filtering error compensation technology is used to solve “explosion of complexity” problem and compensation signals are utilized to abate the influence of filtering errors. And stochastic Lyapunov functions are selected to analyze the stability of the system. In addition, the iron losses and input saturation for PMSMs in EV stochastic drive systems are considered, which makes the designed controller more practical. Finally, the effectiveness of the approach is intuitively illustrated by simulation results.