Multi-model predictive control based on the Takagi-Sugeno fuzzy models: a case study

被引:86
作者
Li, N [1 ]
Li, SY
Xi, YG
机构
[1] Shanghai Jiao Tong Univ, Inst Automat, Shanghai 200030, Peoples R China
[2] E China Univ Sci & Technol, Res Ctr Ind Automat, Shanghai 200237, Peoples R China
基金
中国国家自然科学基金;
关键词
multiple model predictive control (MMPC); Takagi-Sugeno (T-S) models; fuzzy satisfactory clustering (FSC); parallel distribution compensation (PDC);
D O I
10.1016/j.ins.2003.10.011
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Multiple model predictive control (MMPC) strategy based on the Takagi-Sugeno (T-S) model is proposed in this paper. A T-S modeling method using fuzzy satisfactory clustering (FSC) algorithm is introduced at first. FSC is designed to help quickly determine satisfactory number of rules of a T-S model. Based on the T-S model, MMPC strategy is presented using parallel distribution compensation (PDC) method, i.e. different predictive controllers are designed for different rules (local sub-systems). The global controller output is the fuzzy weighted integration of local ones. MMPC with system constraints are also considered in this paper. The presented modeling and controller design procedure is demonstrated on an MIMO simulated pH neutralization process. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:247 / 263
页数:17
相关论文
共 19 条
[1]  
BABUSKA B, 1998, FUZZY MODELING CONTR
[2]  
Banerjee A., 1997, MULTIPLE MODEL APPRO
[3]  
Bhat N. V., 1990, IEEE Control Systems Magazine, V10, P24, DOI 10.1109/37.55120
[4]   SELF-TUNING CONTROL OF A PH-NEUTRALIZATION PROCESS [J].
BUCHHOLT, F ;
KUMMEL, M .
AUTOMATICA, 1979, 15 (06) :665-671
[5]  
Gustafson D. E., 1979, Proceedings of the 1978 IEEE Conference on Decision and Control Including the 17th Symposium on Adaptive Processes, P761
[6]   DYNAMIC MODELING AND REACTION INVARIANT CONTROL OF PH [J].
GUSTAFSSON, TK ;
WALLER, KV .
CHEMICAL ENGINEERING SCIENCE, 1983, 38 (03) :389-398
[7]  
HALL RC, 1989, AMER CONTR CONF CONF, P1822
[8]  
Johansen TA, 1999, INT J CONTROL, V72, P575
[9]  
Karr C. L., 1993, IEEE Transactions on Fuzzy Systems, V1, P46, DOI 10.1109/TFUZZ.1993.390283
[10]  
Lakshmanan NM, 1999, INT J CONTROL, V72, P659, DOI 10.1080/002071799220849