An optimization algorithm used in PMSM model predictive control

Abstract

To improve the operational performance of Permanent Magnet Synchronous Motors (PMSM), a new voltage optimization algorithm is proposed. This algorithm is based on Particle Swarm Optimization (PSO) and incorporates two improvements: online optimization and secondary optimization. The improved PSO (IPSO) algorithm is applied to Dual-Vector Model Predictive Control (DVMPCC) for simulation and experimental research. The results show that, compared to DVMPCC, with similar speed response, the current ripple is reduced by 16.22% and the steady-state speed fluctuation is reduced by 65.14%. This indicates that the proposed algorithm is feasible and effectively improves the operational performance of the system.