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基于灰狼优化算法的双星感应电机最优三阶滑模控制器

Optimal third-order sliding mode controller for dual star induction motor based on grey wolf optimization algorithm.

作者信息

Terfia Es-Saadi, Mendaci Sofiane, Rezgui Salah Eddine, Gasmi Hamza, Kantas Walid

机构信息

Laboratory of Electrical Engineering of Guelma (LGEG), Department of Electrotechnical and Automatic Engineering, Université 8 Mai 1945, Guelma, 24000, Algeria.

Laboratoire D'Automatique et Informatique de Guelma (LAIG), Department of Electrical Engineering, Université 8 Mai 1945, Guelma, 24000, Algeria.

出版信息

Heliyon. 2024 Jun 7;10(12):e32669. doi: 10.1016/j.heliyon.2024.e32669. eCollection 2024 Jun 30.

DOI:10.1016/j.heliyon.2024.e32669
PMID:39183859
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11341324/
Abstract

This paper introduces a novel approach for controlling a dual-star induction motor by combining third-order sliding mode control with the grey wolf optimization algorithm (TOSMC-GWO). The primary objective is to enhance motor performance by minimizing overshoot, rise time, settling time, overall response time, and steady-state error, while simultaneously mitigating unwanted oscillations in stator currents, rotor flux, and electromagnetic torque. Specifically, the proposed controller addresses the limitations of the indirect field-oriented control (IFOC) technique when using a classic sliding mode controller (IFOC-SMC). The latter suffers from challenges related to reference speed tracking and generates significant ripples in stator current and torque due to the chattering effect. The idea of this work is to replace the classic sliding mode controller with an improved approach combining TOSMC control with the GWO method that uses the same input variables as the traditional controller. The performance of the proposed method is evaluated using numerical simulations conducted in MATLAB, and the comparison with the conventional strategy is demonstrated by two tests, showing the good performance of the IFOC-TOSMC-GWO technique. Practically, the minimization of stator current and torque oscillations is 82.23 % and 84.61 %, respectively, which shows the superiority of the proposed method compared to the conventional sliding mode controller.

摘要

本文介绍了一种将三阶滑模控制与灰狼优化算法(TOSMC-GWO)相结合的新型双星感应电动机控制方法。主要目标是通过最小化超调量、上升时间、调节时间、整体响应时间和稳态误差来提高电机性能,同时减轻定子电流、转子磁链和电磁转矩中的有害振荡。具体而言,所提出的控制器解决了间接磁场定向控制(IFOC)技术在使用经典滑模控制器(IFOC-SMC)时的局限性。后者存在与参考速度跟踪相关的挑战,并且由于抖振效应在定子电流和转矩中产生显著的纹波。这项工作的思路是用一种改进方法取代经典滑模控制器,该方法将TOSMC控制与GWO方法相结合,且使用与传统控制器相同的输入变量。利用在MATLAB中进行的数值模拟对所提出方法的性能进行了评估,并通过两项测试展示了与传统策略的比较,表明了IFOC-TOSMC-GWO技术的良好性能。实际上,定子电流和转矩振荡的最小化分别为82.23%和84.61%,这表明所提出方法相对于传统滑模控制器的优越性。

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本文引用的文献

1
A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator.基于群体的元启发式优化技术及其在双馈感应发电机中的应用综述。
Heliyon. 2022 Oct 7;8(10):e10956. doi: 10.1016/j.heliyon.2022.e10956. eCollection 2022 Oct.