Paper
16 August 2023 Dual-parameter collaborative intelligent optimal control of chaotic motion of permanent magnet synchronous motor
Author Affiliations +
Proceedings Volume 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023); 127870H (2023) https://doi.org/10.1117/12.3004883
Event: 6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023), 2023, Shenyang, China
Abstract
Aiming at the chaos control of permanent magnet synchronous motor, a dual-parameter collaborative intelligent optimal control method based on GWO-RBFNN was proposed. Starting from the perspective that the controller can automatically search for the expected motion state, the distance between two points on the Poincaré cross section is selected as the controller input. And considering the coupling effect of system parameters on the dynamic behavior of the system, a dualparameter cooperative controller is designed based on radial basis function neural network (RBFNN); Grey Wolf Optimization (GWO) algorithm is used to optimize the selection of controller parameters; By slightly adjusting the two controllable parameters of the system, the chaotic motion of the PMSM system is controlled to the expected motion state. In the simulation study, compared with the single-parameter intelligent optimization control method based on GWO-RBFNN, the results show that although both methods can achieve chaotic motion control, the control speed of the dual-parameter collaborative intelligent optimization control method based on GWO-RBFNN is faster and overshoot is smaller.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Sixuan Qiu, Ningzhou Li, Xiaojuan Wei, and Gaosong Li "Dual-parameter collaborative intelligent optimal control of chaotic motion of permanent magnet synchronous motor", Proc. SPIE 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023), 127870H (16 August 2023); https://doi.org/10.1117/12.3004883
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KEYWORDS
Control systems

Complex systems

Motion controllers

Chaos

Mathematical optimization

Device simulation

Neural networks

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