文献类型：期刊文献

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

作者：Li, Ning[1,2]; Li, Shao-Yuan[1]; Xi, Yu-Geng[1]

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

年份：2004

卷号：165

期号：3-4

起止页码：247

外文期刊名：INFORMATION SCIENCES

收录：;EI(收录号：2004438423976);WOS:【SCI-EXPANDED(收录号:WOS:000224637600007)】；

语种：英文

外文关键词：multiple model predictive control (MMPC); Takagi-Sugeno (T-S) models; fuzzy satisfactory clustering (FSC); parallel distribution compensation (PDC)

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.