Intelligent power control of wind conversion system based on Takagi-Sugeno fuzzy model

被引:4
|
作者
Abderrahim, Sahbi [1 ]
Allouche, Moez [2 ]
Chaabane, Mohamed [2 ]
机构
[1] Univ Gabes, Natl Sch Engineers Gabes, Res Lab Numer Control Ind Proc, Gabes 6029, Tunisia
[2] Natl Engn Sch Sfax, Lab Sci & Tech Automat Control & Comp Engn Lab STA, Sfax, Tunisia
关键词
boost converter; H performance; T-S model; wind conversion system; POINT TRACKING; TURBINE; DESIGN; MPPT;
D O I
10.1002/cta.3517
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper comes up with a novel fuzzy control design for a wind conversion system (WCS). To do this, a boost converter is employed to adjust the rectified voltage under different wind speed levels. Initially, the boost converter model is well presented via the Takagi-Sugeno approach. Then, a T-S fuzzy controller is designed to promptly calculate the duty cycle required for an optimal power operation. Afterward, the optimal DC current is determined and then transferred to the reference model to instantly determine the desired trajectories. These latter should be preserved so as to reach the maximum power. Following that, linear matrix inequalities (LMIs) are also used to guarantee the stability analyses and the H performance. Finally, the sound performance and the validity of the suggested control schema are both proved by a numerical and some experimental results.
引用
收藏
页码:2247 / 2265
页数:19
相关论文
共 50 条
  • [1] Optimal constant power control of wind turbine generators based on Takagi-Sugeno fuzzy model
    Qin, Shengsheng
    Ngu, SzeSong
    Zeng, Tingting
    ALEXANDRIA ENGINEERING JOURNAL, 2022, 61 (08) : 5977 - 5982
  • [2] Integral control system of nuclear reactor power based on takagi-sugeno fuzzy model
    Luan, Xiuchun
    Zhou, Jie
    Yang, Aimin
    Zhai, Yu
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2013, 33 (02): : 105 - 111
  • [3] Multivariable integral control system based on Takagi-Sugeno fuzzy model
    Luan, Xiu-Chun
    Han, Wei-Shi
    Young, Ai-Guang
    Zhai, Yu
    Jiang, Yu
    PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 1321 - +
  • [4] Sensorless wind energy conversion system maximum power point tracking using Takagi-Sugeno fuzzy cerebellar model articulation control
    Liu, Peter
    Yang, Wen-Tsung
    Yang, Chang-En
    Hsu, Chia-Lien
    APPLIED SOFT COMPUTING, 2015, 29 : 450 - 460
  • [5] H∞ control for NRPCS based on the Takagi-Sugeno fuzzy model
    Gong, Cheng
    Lecture Notes in Electrical Engineering, 2015, 334 : 935 - 941
  • [6] Fuzzy Control Based on New Type of Takagi-Sugeno Fuzzy Inference System
    Anikin, Igor V.
    Zinoviev, Igor P.
    2015 INTERNATIONAL SIBERIAN CONFERENCE ON CONTROL AND COMMUNICATIONS (SIBCON), 2015,
  • [7] Robust Takagi-Sugeno Fuzzy Control of PV System
    Kamal, Elkhatib
    Aitouche, Abdel
    Bouamama, Belkacem Ould
    2016 INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT), 2016, : 52 - 58
  • [8] Sliding Mode Control of Nonlinear Uncertain System Based on Takagi-Sugeno Fuzzy Model
    Chaouech, Lotfi
    Saadaoui, Oussama
    Chaari, Abdelkader
    2013 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND SOFTWARE APPLICATIONS (ICEESA), 2013, : 220 - 225
  • [9] Design of Sliding Mode Control of Nonlinear System Based on Takagi-Sugeno Fuzzy Model
    Chaouech, Lotfi
    Chaari, Abdelkader
    WORLD CONGRESS ON COMPUTER & INFORMATION TECHNOLOGY (WCCIT 2013), 2013,
  • [10] A fuzzy radon replenishment control method based on Takagi-Sugeno model
    Zhou Shumin
    Tang Bin
    Tang Fangdong
    Wang Zhenji
    Zhang Jun
    SEVENTH INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION AND CONTROL TECHNOLOGY: OPTOELECTRONIC TECHNOLOGY AND INSTUMENTS, CONTROL THEORY AND AUTOMATION, AND SPACE EXPLORATION, 2008, 7129