Investigation of chaotic behavior and adaptive type-2 fuzzy controller approach for Permanent Magnet Synchronous Generator (PMSG) wind turbine system-Reference-Cited by-同舟云学术

Investigation of chaotic behavior and adaptive type-2 fuzzy controller approach for Permanent Magnet Synchronous Generator (PMSG) wind turbine system

Published:2022 Issue:3 Volume:8 Page:5670-5686
ISSN:2473-6988
Container-title:AIMS Mathematics
language:
Short-container-title:MATH

Author:

Sambas Aceng¹²,Mohammadzadeh Ardashir³,Vaidyanathan Sundarapandian⁴,Mohamad Ayob Ahmad Faisal²,Aziz Amiral⁵,Mohamed Mohamad Afendee⁶,Sulaiman Ibrahim Mohammed⁷,Nawi Mohamad Arif Awang⁸

Affiliation:

1. Department of Mechanical Engineering, Universitas Muhammadiyah Tasikmalaya, Tasikmalaya, Jawa Barat 46196, Indonesia

2. Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, Malaysia

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

4. Centre for Control Systems, Vel Tech University, Vel Nagar, Avadi, Chennai 600 062, Tamil Nadu

5. Research Center for Conversion and Conservation Energy-National Research and Innovation Agency Republic of Indonesia (BRIN), South Tangerang 15314, Indonesia

6. Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Terengganu, Malaysia

7. School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah 06010, Malaysia

8. School of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kelantan 16150, Malaysia

Abstract

<abstract> <p>This article begins with a dynamical analysis of the Permanent Magnet Synchronous Generator (PMSG) in a wind turbine system with quadratic nonlinearities. The dynamical behaviors of the PMSG are analyzed and examined using Poincare map, bifurcation model, and Lyapunov spectrum. Finally, an adaptive type-2 fuzzy controller is designed for different flow configurations of the PMSG. An analysis of the performance for the proposed approach is evaluated for effectiveness by simulating the PMSG. In addition, the proposed controller uses advantages of adaptive type-2 fuzzy controller in handling dynamic uncertainties to approximate unknown non-linear actions.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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