Velocity control of a PMLSM using a brain emotional learning based intelligent control strategy

Abstract

A velocity controller for a permanent magnet linear synchronous motor (PMLSM) is designed using a brain emotional learning based intelligent control (BELBIC). This is performed for a comprehensive nonlinear model of PMLSM including non-idealities such as detent force, parameter uncertainty, unpredicted disturbance, and nonlinear friction. As an evaluation criterion of the performance of the proposed method, a proportional - integral (PI) controller is designed whose parameters are optimally tuned by the particle Swarm Optimization (PSO) algorithm for better comparison.