Multiple-Model Based Linear Parameter Varying Time-Delay System Identification with Missing Output Data Using an Expectation-Maximization Algorithm

被引:27
|
作者
Xiong, Weili [1 ,2 ]
Yang, Xianqiang [2 ,3 ]
Huang, Biao [2 ]
Xu, Baoguo [1 ]
机构
[1] Jiangnan Univ, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Jiangsu, Peoples R China
[2] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2G6, Canada
[3] Harbin Inst Technol, Res Inst Intelligent Control & Syst, Harbin 150080, Heilongjiang, Peoples R China
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
Impulse response - Delay control systems - Maximum principle - FIR filters - Parameter estimation - Image segmentation - Timing circuits;
D O I
10.1021/ie500175r
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This paper is concerned with the identification problems of the linear parameter varying (LPV) system with missing output in the presence of the time-delay. A multiple-model approach is adopted. Local models varying from one operating point to another are first described by finite impulse response (FIR) models. To handle missing output and time-delay, the expectation-maximization (EM) algorithm is utilized to estimate the unknown parameters and the time-delay simultaneously. Output Error (OE) models are widely used in controller design. Therefore, the auxiliary model principle is employed to recover the OE models based on the initially identified FIR models. The EM algorithm is then used again to refine the unknown parameters of the OE models with the complete data set to obtain the final global model. Simulation examples are presented to demonstrate the performance of the proposed method.
引用
收藏
页码:11074 / 11083
页数:10
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