Design of a Deflection Switched Reluctance Motor Control System Based on a Flexible Neural Network

Zheng Li, Xiaopeng Wei, Jinsong Wang, Libo Liu, Shenhui Du, Xiaoqiang Guo and Hexu Sun
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Zheng Li: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Xiaopeng Wei: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Jinsong Wang: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Libo Liu: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Shenhui Du: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Xiaoqiang Guo: School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
Hexu Sun: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China

Energies, 2022, vol. 15, issue 11, 1-16

Abstract: Deflection switched reluctance motors (DSRM) are prone to chattering at low speeds, which always affects the output efficiency of the DSRM and the mechanical loss of the motor. Combining the characteristics of a traditional reluctance motor with the strong nonlinear and high coupling of the DSRM, a control system for a DSRM based on a flexible neural network (FNN) is proposed in this paper. Based on the better robustness and fault tolerance of fuzzy PI control, the given speed signal is adjusted and converted into a torque control signal. As a result, the FNN control module possesses the strong self-learning ability and adaptive adjustment ability necessary to obtain the control voltage signal. Through simulations and experiments, it was verified that the control system can run stably on DSRM and shows good dynamic performance and anti-interference ability.

Keywords: switched reluctance motor; flexible neural network; fuzzy controller; deflection type (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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