An efficient hierarchical identification method for general dual-rate sampled-data systems |
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Authors: | Yanjun Liu Feng Ding Yang Shi |
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Affiliation: | 1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China;2. Control Science and Engineering Research Center, Jiangnan University, Wuxi 214122, China;3. Department of Mechanical Engineering, University of Victoria, Victoria, Canada, V8W 3P6 |
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Abstract: | For the lifted input–output representation of general dual-rate sampled-data systems, this paper presents a decomposition based recursive least squares (D-LS) identification algorithm using the hierarchical identification principle. Compared with the recursive least squares (RLS) algorithm, the proposed D-LS algorithm does not require computing the covariance matrices with large sizes and matrix inverses in each recursion step, and thus has a higher computational efficiency than the RLS algorithm. The performance analysis of the D-LS algorithm indicates that the parameter estimates can converge to their true values. A simulation example is given to confirm the convergence results. |
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Keywords: | Parameter estimation Recursive identification Least squares Hierarchical identification principle Dual-rate system Multirate system |
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