Super-twisting sliding-mode observer-based model reference adaptive speed control for PMSM drives

被引:30
作者
Liu, Yong-Chao [1 ]
Laghrouche, Salah [1 ]
Depernet, Daniel [1 ]
N'Diaye, Abdoul [1 ]
Djerdir, Abdesslem [1 ]
Cirrincione, Maurizio [2 ]
机构
[1] Univ Bourgogne Franche Comte, UTBM, CNRS, Energy Dept,FEMTO ST Inst UMR 6174, Belfort, France
[2] Univ South Pacific, Sch Informat Technol Engn Math & Phys, Laucala Campus, Suva, Fiji
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2023年 / 360卷 / 02期
关键词
TRACKING;
D O I
10.1016/j.jfranklin.2022.12.014
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper develops a super-twisting sliding-mode observer-based model reference adaptive speed controller (STSMO-MRA-SC) for the permanent-magnet synchronous motor-based variable speed drive (PMSM-VSD) system. A stable first-order linear model is selected as the reference model to describe the required speed trajectory. To make the actual speed of the PMSM-VSD system follow this trajectory, the proposed STSMO-MRA-SC comprises three terms: (1) the stabilization term dependent on known parameters of the motion dynamics and the selected reference model for stabilizing the speed tracking error dynamics asymptotically; (2) the disturbance compensation term based on the STSMO for compensating the lumped disturbance in the speed tracking error dynamics; and (3) the error compensation term updated online by the adaptive law for confronting the estimation error of the STSMO in practice. Comparative experimental tests among the classic MRA-SC, the radial basis function neural network-based MRA-SC and the proposed STSMO-MRA-SC are performed. Experimental results have verified the effectiveness and the superiority of the proposed STSMO-MRA-SC. (c) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:985 / 1004
页数:20
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