Electrical & Electronic Engineering |
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Subspace identification for continuous-time errors-in-variables model from sampled data |
Ping WU, Chun-jie YANG, Zhi-huan SONG |
State Key Lab of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China |
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Abstract We study the subspace identification for the continuous-time errors-in-variables model from sampled data. First, the filtering approach is applied to handle the time-derivative problem inherent in continuous-time identification. The generalized Poisson moment functional is focused. A total least squares equation based on this filtering approach is derived. Inspired by the idea of discrete-time subspace identification based on principal component analysis, we develop two algorithms to deliver consistent estimates for the continuous-time errors-in-variables model by introducing two different instrumental variables. Order determination and other instrumental variables are discussed. The usefulness of the proposed algorithms is illustrated through numerical simulation.
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Received: 30 September 2008
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