Command Filtered Fuzzy Adaptive Control for PMSMs With Time-Varying State Constraints and Stochastic Disturbances

To fulfill the high-performance demands for permanent magnet synchronous motors (PMSMs) in transportation applications, a time-varying barrier Lyapunov function (BLF)-based command filtered fuzzy adaptive controller is presented for PMSMs with stochastic disturbances. First, the time-varying log-type BLF is utilized to ensure that all the state variables of PMSM stochastic systems, such as the stator current and rotor speed, will remain in the time-varying constraints. Then, the unknown stochastic nonlinear functions in PMSMs’ stochastic systems are approximated by the fuzzy logic systems (FLSs), and a reduced-order observer is constructed for estimating the angular velocity. In addition, the command filter and error compensation are employed to solve the issue of “explosion of complexity”(EOC) and offset the influence of filtering errors. Finally, it is shown that all the signals in the closed-loop system are bounded. The simulation and experimental studies are given to confirm the effectiveness of the controller.