Full state constraints and command filtering-based adaptive fuzzy control for permanent magnet synchronous motor stochastic systems.

• The stochastic disturbance in motor operation is considered. • The problem of "explosion of complexity" is solved by using the command filtering technique. • The error compensation mechanism is introduced to reduce filtering errors. • The barrier Lyapunov function is introduced to ensure that the full state constraints are not violated. In this article, an adaptive fuzzy control scheme based on command filtering is proposed for the position tracking control of permanent magnet synchronous motor (PMSM) stochastic system with full state constraints. Firstly, fuzzy logic systems are employed to approximate unknown stochastic nonlinear functions in PMSM stochastic system. Then, the barrier Lyapunov functions are constructed to ensure that all states of the system do not violate its constrained boundary. In addition, the problem of "explosion of complexity" in traditional backstepping design is solved by using the command filtering technique and the error compensation mechanism is introduced to reduce filtering errors. At last, the effectiveness of the scheme is illustrated by simulation results. [ABSTRACT FROM AUTHOR]