Genetic Algorithm approach for the Position Control of Permanent Magnetic Synchronous Machine

Abstract

Permanent Magnetic Synchronous Motors (PMSM or Brushless DC Motor) are widely being used for many industrial applications because of their high efficiency, high torque and low volume. Research has conducted using genetic algorithm to develop a complete model of the BLDC motor and to design an optimal controller for its position control. Generally PID controller is being used for control purposes in many systems because of its simple structure and easy implementation. However, in practice, we often do not get the optimum performance with the conventionally tuned PID controllers. For this purpose, Artificial Intelligence based Genetic Algorithm is proposed as an optimizer to find the optimized PID gains for the position control of PMSM motor. Comparison was made with the traditional method. Simulation results showed that PID control tuned by GA provides more efficient closed loop response for position control of PMSM motor. MATLAB/SIMULINK software package was used for the modelling, control and simulation of the PMSM motor.