Probabilistic PCA Based Spatio-Temporal Multi-Modeling for Distributed Parameter Processes

作     者：QI Chenkun~1,LI Han-Xiong~2,ZHANG Xian-Xia~3,ZHAO Xianchao~1,LI Shaoyuan~4,GAO Feng~1 1.School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,P.R.China 2.Department of Manufacturing Engineering & Engineering Management,City University of Hong Kong,Hong Kong 3.Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronics and Automation,Shanghai University, Shanghai 200072,P.R.China 4.Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,P.R.China 

会议名称：《第三十届中国控制会议》

会议日期：2011年

学科分类：0711[理学-系统科学] 07[理学] 071102[理学-系统分析与集成] 

基　　金：supported by National Nature Science Foundation of China (60825302,61004047,60804033) a RGF project from RGC of Hong Kong (CityU 117310) a SRG project from City University of Hong Kong(7002562) Specialized Research Fund for the Doctoral Program of Higher Education of China(20100073120045) 

关 键 词：Distributed parameter system Spatio-temporal modeling Multi-modeling Probabilistic PCA 

摘      要：正Data-based modeling of unknown distributed parameter systems（DPSs） is very challenging due to their infinite-dimensional,nonlinear and even time-varying *** get a low-order model for applications,the principal component analysis（PCA） is often ***,as a linear dimension reduction,it only leads to one set of fixed spatial *** a good performance for nonlinear and time-varying DPSs could not be *** this study,a probabilistic PCA based spatio-temporal multi-modeling is *** to its multi-modeling mechanism,a better performance can be achieved,which is demonstrated by simulations.