Adaptive Inverse Control Based on MPSO-ANFIS for Permanent Magnet Synchronous Motor Servo System

This paper proposes a novel adaptive inverse control for permanent magnet synchronous motor (PMSM) servo system. Due to the time varying and the high-bandwidth property of the uncertainties in a practical PMSM servo system, to reach exact position control in PMSM servo system, the position loop adopts adaptive inverse control strategy based on Adaptive Network based Fuzzy Inference System (ANFIS). This paper adopts ANFIS get the model and inverse model of PMSM servo system. This novel algorithm is based on microhabitat particle swarm optimization (MPSO) for training the parameters of ANFIS. This control strategy make set signal, parameter disturbance and external disturbance separately controlled and make them reach the optimal control without compromise. Finally initial convergence speed, tracking ability and steady precision of PMSM servo system and inverse system reach optimal simultaneous. The performance of the servo system was evaluated through simulation and real time implementation and experimental results validate the effectiveness.