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Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition 被引量:2

基于奇异值分解递推辨识非均匀采样系统的状态空间模型(英文)
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摘要 In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of state measurement, an identification algorithm based on the singular value decomposition(SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method. In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of state measurement, an identification algorithm based on the singular value decomposition(SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method.
作者 王宏伟 刘涛
出处 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第Z1期1268-1273,共6页 中国化学工程学报(英文版)
基金 Supported in part by the National Thousand Talents Program of China the National Natural Science Foundation of China(61473054) the Fundamental Research Funds for the Central Universities of China
关键词 Non-uniformly sampling system STATE-SPACE model IDENTIFICATION SINGULAR value decomposition RECURSIVE algorithm Non-uniformly sampling system State-space model identification Singular value decomposition Recursive algorithm
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参考文献7

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二级参考文献22

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