Fuzzy predictive control based on T-S model

被引:0
|
作者
Xing, Zong-Yi [1 ]
Hu, Wei-Li [1 ]
Jia, Li-Min [2 ]
机构
[1] Department of Automatic, Nanjing University of Science and Technology, Nanjing 210094, China
[2] School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
来源
Kongzhi yu Juece/Control and Decision | 2005年 / 20卷 / 05期
关键词
Computer simulation - Fuzzy sets - Matrix algebra - Nonlinear systems - Optimization - Quadratic programming - Time varying systems;
D O I
暂无
中图分类号
学科分类号
摘要
A fuzzy model based predictive control of nonlinear system is presented. T-S fuzzy model is identified by fuzzy clustering algorithm, and its parameters are self-learning online by selective recursive least square method. T-S model is linearized to be time-varying system, and thus nonlinear optimization problem is turned to a quadratic programming problem. Consequently, two major difficulties in nonlinear predictive control to obtain accurate nonlinear model and to solve nonlinear optimization problem online are solved. The simulation result on pH neutralization process shows the effectiveness of the proposed method.
引用
收藏
页码:495 / 499
相关论文
共 50 条
  • [31] 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
  • [32] Locomotive Brake Control Method based on T-S Fuzzy Modeling Predictive Control
    Liu, Jianfeng
    Huang, Zhiwu
    Liu, Weirong
    Yang, Yingze
    Tong, Haitao
    2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL III, PROCEEDINGS, 2008, : 602 - 607
  • [33] Study on state feedback fuzzy-predictive control system of T-S fuzzy model
    Wang, Shubin
    Hu, Pinhui
    Lin, Li
    ICICIC 2006: FIRST INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING, INFORMATION AND CONTROL, VOL 2, PROCEEDINGS, 2006, : 179 - +
  • [34] Predictive Control Algorithm for Urban Rail Train Brake Control System Based on T-S Fuzzy Model
    Wang, Xiaokan
    Wang, Qiong
    Liang, Shuang
    CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 64 (03): : 1859 - 1867
  • [35] Dynamic Event-Based Model Predictive Control of IT2 T-S Fuzzy System
    Rong, Nannan
    Wang, Bohan
    Zhang, Xiaowei
    Ji, Yue
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2024, 71 (02) : 692 - 696
  • [36] Stability analysis of T-S fuzzy-model-based coupled control systems with nonlinear T-S fuzzy control and its application
    Liu, Jiayi
    Cui, Yongmei
    Song, Huihui
    Zhang, Xuewei
    Qu, Yanbin
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (22): : 15481 - 15493
  • [37] T-S Fuzzy Model Predictive Control for Vehicle Yaw Stability in Nonlinear Region
    Wei, Lingtao
    Wang, Xiangyu
    Li, Liang
    Fan, Zhixian
    Dou, Ruzhen
    Lin, Jingui
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (08) : 7536 - 7546
  • [38] T-S Fuzzy Model Generalized Predictive Control of High-Speed Train
    Yang, Hui
    Fu, Yating
    Zhang, Kunpeng
    Li, Zhongqi
    INNOVATION AND SUSTAINABILITY OF MODERN RAILWAY, 2012, : 394 - 398
  • [39] Control System based on Affine T-S Fuzzy Model with Uncertainty
    Han, Hugang
    2020 JOINT 11TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS AND 21ST INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (SCIS-ISIS), 2020, : 431 - 436
  • [40] Stability analysis of T-S fuzzy-model-based coupled control systems with nonlinear T-S fuzzy control and its application
    Jiayi Liu
    Yongmei Cui
    Huihui Song
    Xuewei Zhang
    Yanbin Qu
    Neural Computing and Applications, 2021, 33 : 15481 - 15493