Design of fuzzy PI controller for brushless DC motor based on PSO–GSA algorithm

• Main Authors: Baoye Song, Yihui Xiao, Lin Xu
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2020-01-01
• Series: Systems Science & Control Engineering
• Subjects: brushless dc motor; fuzzy pi controller; particle swarm optimization; gravitational search algorithm; pso; gsa
• Online Access: http://dx.doi.org/10.1080/21642583.2020.1723144

To design an optimal fuzzy proportional-integral (PI) controller for brushless DC motor (BLDCM), a random vibration particle swarm optimization (PSO)–gravitational search algorithm (GSA)-based approach is developed in this paper. By introducing a random vibration term, the PSO–GSA, which combines the advantages of PSO and GSA, can obtain more power to exploit the search space around the local minima and/or jump out of the local trapping to explore the whole search space more thoroughly. Several simulation tests are implemented on benchmark functions and confirm the superiority of the proposed PSO–GSA in comparison with PSO and GSA. The developed PSO–GSA is then applied to design an optimal fuzzy PI controller for BLDCM, whose parameters can be optimally selected to obtain better performance. Finally, the performance of the proposed approach can be verified by several simulation and experimental results on BLDCM control.