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

摘要：

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

作者: QI Chenkun LI Han-Xiong ZHANG Xian-Xia ZHAO Xianchao LI Shaoyuan GAO Feng

作者单位: School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,P.R.China Department of Manufacturing Engineering &Engineering Management,City University of Hong Kong,Hong Ko Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronics and Automation Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,P.R.China

会议类型: 国际会议

会议名称: The 30th Chinese Control Conference(第三十届中国控制会议)

会议地点: 烟台

会议语种:英文

页码: 1-6

在线出版日期: 2011-07-01（万方平台首次上网日期，不代表论文的发表时间）