Changchun Institute of Optics,Fine Mechanics and Physics,CAS
Fast integral terminal sliding mode control with a novel disturbance observer based on iterative learning for speed control of PMSM | |
T. Yang; Y. Deng; H. Li; Z. Sun; H. Cao and Z. Wei | |
2022 | |
ISSN | 00190578 |
摘要 | This study revolves about the speed control of a permanent magnet synchronous motor (PMSM) with torque ripple and external disturbance. To enhance the performance of the PMSM speed control in response, robustness and torque ripple suppression, a hybrid control technique is presented by combining a novel disturbance observer based on iterative learning strategy (ILC-DOB) and a fast integral terminal sliding mode control (FITSMC) method. Firstly, an iterative learning law is used to enhance the conventional high-gain disturbance observer (DOB) to improve the estimation performance for periodic disturbance. Then, a new fast integral terminal sliding mode surface is proposed to increase the tracking error convergent speed of the traditional integral terminal sliding mode control (ITSMC) when the speed error is distant from the equilibrium point. Finally, the estimated total disturbance is incorporated as a feed-forward compensation to the enhanced FITSMC. According to experimental results, the presented method can ensure better speed-tracking performance and significant disturbance rejection capability of the PMSM drive system. 2022 ISA |
DOI | 10.1016/j.isatra.2022.07.029 |
URL | 查看原文 |
收录类别 | ei |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ciomp.ac.cn/handle/181722/66664 |
专题 | 中国科学院长春光学精密机械与物理研究所 |
推荐引用方式 GB/T 7714 | T. Yang,Y. Deng,H. Li,et al. Fast integral terminal sliding mode control with a novel disturbance observer based on iterative learning for speed control of PMSM[J],2022. |
APA | T. Yang,Y. Deng,H. Li,Z. Sun,&H. Cao and Z. Wei.(2022).Fast integral terminal sliding mode control with a novel disturbance observer based on iterative learning for speed control of PMSM.. |
MLA | T. Yang,et al."Fast integral terminal sliding mode control with a novel disturbance observer based on iterative learning for speed control of PMSM".(2022). |
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