Abstract
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.
Highlights
With the rapid development of modern power electronics and modern control theory, brushless DC motor (BLDCM) is widely utilized in various industrial fields due to some of its advantages, such as high power density, superior speed regulation and high reliability, to name but just a few (Ji, Shen, & Xue, 2005; Xia, Zhang, & Wang, 2008)
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
A fuzzy PI controller has been designed in Wen and Ma (2016) to achieve real-time speed control of BLDCM, but the initial parameters of the PI controller are still regulated by hand
Summary
With the rapid development of modern power electronics and modern control theory, brushless DC motor (BLDCM) is widely utilized in various industrial fields due to some of its advantages, such as high power density, superior speed regulation and high reliability, to name but just a few (Ji, Shen, & Xue, 2005; Xia, Zhang, & Wang, 2008). In Jing, Wang, and Zhu (2018), a fuzzy adaptive PID controller has been presented for the control of BLDCM, where the domain of the fuzzy controller can be adaptively altered to obtain a perfect static performance, while the speed fluctuation cannot be well suppressed. To handle the problems identified above, a random vibration PSO–GSA algorithm-based approach is presented to design an optimal fuzzy PI controller for BLDCM. By combining the global exploring ability of PSO with the local exploiting ability of GSA as well as a term of random vibration, the proposed PSO–GSA algorithm performs an excellent optimum searching ability on the parameter optimization problem of the fuzzy PI controller. (2) The developed PSO–GSA algorithm is employed to design a fuzzy PI controller for BLDCM, whose parameters can be optimally selected to obtain better performance in simulation.
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