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《中国化学工程学报(英文版)》 2012-06
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An Extended Closed-loop Subspace Identification Method for Error-in-variables Systems

LIU Tao ** and SHAO Cheng Institute of Advanced Control Technology, Dalian University of Technology, Dalian 116024, China  
A closed-loop subspace identification method is proposed for industrial systems subject to noisy input-output observations, known as the error-in-variables (EIV) problem. Using the orthogonal projection approach to eliminate the noise influence, consistent estimation is guaranteed for the deterministic part of such a system. A strict proof is given for analyzing the rank condition for such orthogonal projection, in order to use the principal component analysis (PCA) based singular value decomposition (SVD) to derive the extended observability matrix and lower triangular Toeliptz matrix of the plant state-space model. In the result, the plant state matrices can be retrieved in a transparent manner from the above matrices. An illustrative example is shown to demonstrate the effectiveness and merits of the proposed subspace identification method.
【Fund】: Supported in part by Chinese Recruitment Program of Global Young Expert Alexander von Humboldt Research Fellowship of Germany the Foundamental Research Funds for the Central Universities;; the National Natural Science Foundation of China (61074020)
【CateGory Index】: N945.14
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