Constrained Predictive Position Control of the Planar Switched Reluctance Motor Using Threshold Function

• Published in: 2020 10th Institute of Electrical and Electronics Engineers International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) pp. 307 - 311
• Main Authors: Xu, Zhi-Hui, Huang, Su-Dan, Cao, Guang-Zhong, Sun, Jun-Di, Jing, Gang, Liu, Yan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10.10.2020
• Subjects: Electromagnetics; Force; Optimal control; Predictive models; Steady-state; Switched reluctance motors; Trajectory tracking
• DOI: 10.1109/CYBER50695.2020.9278961

To achieve satisfactory positioning performance considering actuator saturation, this article proposes a constrained predictive position control (CPPC) approach using the threshold function for the planar switched reluctance motor (PSRM). For the PSRM designed in our lab, a dynamic model expressed as a discrete state-space model is established. The input thrust force of the position controller is constrained by applying a nonlinear threshold function. Based on the constrained thrust force, a prediction model with constraints, which can predict motor positions in the future, is built. With the cost function developed from the prediction model, the control input is derived through minimizing the cost function. Finally, the results of experiments demonstrate the presented CPPC can availably restrain the input thrust force as well as realize the satisfactory positioning performance of the PSRM.