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9 August 2024 Research on current tracking error elimination algorithm for permanent magnet synchronous motor based on temporal convolutional networks
Yuejuan Huang, Huili Hou, Yuting Zhu, Mengting Xu, Fanju Zeng
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Proceedings Volume 13220, Third International Conference on Mechatronics and Mechanical Engineering (ICMME 2024); 1322012 (2024) https://doi.org/10.1117/12.3039410
Event: International Conference on Mechatronics and Mechanical Engineering (ICMME 2024), 2024, Xi'an, China
Abstract
Current tracking error is a primary factor limiting motor control performance. This paper addresses this issue in model predictive control systems without integral controllers, using deadbeat predictive control as an example. Initially, the causes of current tracking error are analyzed to elucidate the fundamental reasons for its occurrence under model predictive control. This understanding is crucial for developing effective solutions. Leveraging the rapid convergence of Temporal Convolutional Networks (TCN), a TCN-based algorithm is proposed to eliminate current tracking error. TCNs are chosen for their quick adaptation capabilities, essential in dynamic motor control environments. By evaluating the motor's actual operating conditions, specific causes of current tracking error are identified. To address these swiftly, a voltage feedforward method is employed, allowing for rapid error elimination. This approach ensures the system can respond promptly to changes, maintaining precise control. Experimental results validate the proposed method's effectiveness, demonstrating its ability to eliminate current tracking error in model predictive control systems. Consequently, this significantly enhances the motor's load-carrying capacity at high speeds. The findings highlight the potential of the TCN-based algorithm to improve motor performance, marking a valuable advancement in motor control technology.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yuejuan Huang, Huili Hou, Yuting Zhu, Mengting Xu, and Fanju Zeng "Research on current tracking error elimination algorithm for permanent magnet synchronous motor based on temporal convolutional networks", Proc. SPIE 13220, Third International Conference on Mechatronics and Mechanical Engineering (ICMME 2024), 1322012 (9 August 2024); https://doi.org/10.1117/12.3039410
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KEYWORDS
Control systems
Error analysis
Data modeling
Resistance
Detection and tracking algorithms
Inductance
Mathematical modeling
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