Genetic algorithm optimization for high-performance VSI-fed permanent magnet synchronous motor drives

Nowadays permanent magnet synchronous motor (PMSJVP drives are widely used in many industrial applications. Since most of the PMSM drive systems with closed-loop vector control techniques are controlled with proportional plus integral (PI) controllers, there exists growing demands to obtain optimal P1 gain parameters to achieve high-performance. To eliminate disadvantages of traditional P1 optimization techniques, a novel P1 controller optimization methodology based on the multi-objective genetic algorithm, NSGA-II(non-dominated sorting genetic algorithm II), is proposed in this paper to enhance PMSM drive system performances under various working conditions. With the optimal P1 controller in a speed field oriented control scheme, the current controlled Voltage-Source-Inverter-Fed PMSM (VSI-Fed PMSM) drive system shows outstanding dynamic and steady performances in simulation. Also, a practical PMSM drive system based on digital signal processor (DSP) is built and tested to verify the effectiveness of the multi-objective genetic algorithm optimization methodology for motor drive systems.