Chaos synchronization of brushes direct current motors for electric vehicle: Adaptive fuzzy immersion and invariance approach

Author:

Mohammadzadeh Ardashir1,Ahmadian Ali1ORCID,Elkamel Ali23,Alhameli Falah24

Affiliation:

1. Department of Electrical Engineering, University of Bonab, Iran

2. College of Engineering, University of Waterloo, Canada

3. College of Engineering, Khalifa University of Science and Technology, The Petroleum Institute, UAE

4. Abu Dhabi National Oil Company, UAE

Abstract

In this paper, a novel control technique on basis of adaptive immersion and invariance (I&I) theorem and fuzzy systems is proposed to control the brushless direct current motors (BLDCMs) for electric vehicles. The chaotic behaviour of the BDCMs is synchronized with the desired chaotic system. The parameters of the chaotic model are considered to be unknown and are online estimated with tuning rules that are derived through the I&I stability theorem. The effects of the adaptation errors are compensated by the adaptive fuzzy systems. The fuzzy systems are online learned to insure the robustness and stability. The effectiveness and desirable performance of the suggested methodology is verified with both normal simulations and real-time examination. The simulation outcomes of the presented methodology are compared with the some other adaptive methods and it is shown that the presented methodology is more effective.

Publisher

SAGE Publications

Subject

Instrumentation

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Constrained integral fuzzy sliding mode control for an electric vehicle: An LMI-based approach;Transactions of the Institute of Measurement and Control;2022-12-14

2. Control and synchronization of chaotic spur gear system using adaptive non-singular fast terminal sliding mode controller;Transactions of the Institute of Measurement and Control;2022-05-02

3. A type-2 fuzzy control for active/reactive power control and energy storage management;Transactions of the Institute of Measurement and Control;2021-09-28

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