Parameter Identification of Permanent Magnet Synchronous Motors Using Improved Particle Swarm Optimization

This paper introduces an improved particle swarm optimization(IPSO) algorithm and applies this method to parameter identification of permanent magnet synchronous motors(PMSM).The machine dynamics was presented as a set of time-varying differential equations with machine inductances modeled by nonlinear functions of exciting current.For comparison,the results of identification using the genetic algorithm(GA) and the standard particle swarm optimization(SPSO) were also provided.It is concluded that the IPSO algorithm remarkably improves the accuracy of identification parameters and IPSO is more effective for parameter identification of permanent magnet synchronous motors