Command filtering-based adaptive fuzzy control for permanent magnet synchronous motors with full-state constraints

Focusing on the problem of position tracking control for permanent magnet synchronous motors (PMSMs) with full-state constraints, this article proposes an adaptive fuzzy control scheme based on command filtering error compensation mechanism. Firstly, the unknown nonlinear functions of PMSM drive systems are approximated by utilizing the fuzzy logic systems (FLSs). Then, the command filtering technique is employed to deal with the “explosion of complexity” problem arising from conventional backstepping scheme, and the filtering errors are reduced by the error compensation mechanism. In addition, the barrier Lyapunov functions (BLFs) are constructed to guarantee that the state variables are restricted in compact bounding sets. Finally, simulation results show the effectiveness of the proposed scheme.