Fuzzy identification of T-S model for beam stability control for electron gun

被引：0
|
作者：
Lu Bin [1 ]
Su Hai-Jun [1 ]
Li De-Ming [1 ]
机构：
[1] Chinese Acad Sci, Shanghai Inst Appl Phys, Shanghai 201800, Peoples R China
来源：
NUCLEAR SCIENCE AND TECHNIQUES | 2015年 / 26卷 / 05期
关键词：
Electron gun system; T-S fuzzy model; Quantum encoding; Model-based control strategy; CONTROL-SYSTEMS; TRACKING CONTROL; DYNAMIC-SYSTEMS; DESIGN; ISSUES;
D O I：
暂无
中图分类号：
TL [原子能技术]; O571 [原子核物理学];
学科分类号：
0827 ; 082701 ;
摘要：
In this paper, Takagi-Sugeno (T-S) fuzzy control is proposed for stabilizing the output beam of accelerators. To model the nonlinear system, we proposed a hybrid optimization algorithm based on quantum-inspired differential evolution and genetic algorithm. Based on the T-S model identified, the corresponding state-feedback fuzzy controller is designed. The method is applied to the LaB6 electron gun system in the industrial radiation accelerator and the simulation results show its effectiveness.
引用
收藏
页数：7
相关论文
共 50 条
  • [21] Stability of T-S Model Based Fuzzy Control Systems -Virtual Equivalent System Approach
    Zhang, Weicun
    Wang, Xiaobo
    2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PROBLEM-SOLVING (ICCP), 2013, : 90 - 93
  • [22] Stability analysis of T-S fuzzy-model-based control systems using fuzzy Lyapunov function
    Lam, H. K.
    Narimani, M.
    Lai, J. C. Y.
    Leung, F. H. F.
    2008 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5, 2008, : 931 - +
  • [23] Stability analysis for floating structures using T-S fuzzy control
    Chen, Chen-Yuan
    Chen, Cheng-Wu
    Yeh, Ken
    Tseng, Chun-Pin
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2007, 4682 : 750 - 758
  • [24] Stability analysis of T-S fuzzy control systems with interval plants
    曹开锐
    刘佳琦
    黄显林
    高晓智
    班晓军
    Journal of Harbin Institute of Technology(New series), 2012, (01) : 7 - 11
  • [25] Intelligent Control: A T-S Fuzzy Model Based Approach
    Feng, Gang
    PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : XXIV - XXIV
  • [26] MIMO predictive control based on T-S fuzzy model
    Niu, Lin
    Liu, Junyong
    Dianli Zidonghua Shebei / Electric Power Automation Equipment, 2009, 29 (09): : 70 - 72
  • [27] Research of Fuzzy predictive control Based on T-S model
    Zhang, Yong
    Zhang, Zonglong
    PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 4839 - 4844
  • [28] Local Model Predictive Control for T-S Fuzzy Systems
    Lee, Donghwan
    Hu, Jianghai
    IEEE TRANSACTIONS ON CYBERNETICS, 2017, 47 (09) : 2556 - 2567
  • [29] A new approach for online T-S fuzzy identification and model predictive control of nonlinear systems
    Rastegar, Saeid
    Araujo, Rui
    Mendes, Jerome
    JOURNAL OF VIBRATION AND CONTROL, 2016, 22 (07) : 1820 - 1837
  • [30] Identification of aero-engines model based on T-S fuzzy model
    Engineering Inst., Air force Engineering Univ., Xi'an 710038, China
    Tuijin Jishu, 2007, 2 (194-198): : 194 - 198
12345