Parameter identification of a Linear Permanent Magnet motor using Particle Swarm Optimization

Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is to use Particle Swarm Optimization (PSO) algorithm. Linear Permanent Magnet (LPM) motor is a high performance actuator employed in many applications that require direct linear motion without mechanical transmission for high acceleration and accurate positioning. Therefore, accurate motor parameters are necessary to effectively control the LPM motors. This paper proposes a simple PSO based method with chirp inputs to identify the LPM motor's parameters. The simulations and experiments are conducted to verify the results and determine the effectiveness of the proposed method.