Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
695506 | Automatica | 2014 | 9 Pages |
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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Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Yanjun Liu, Feng Ding, Yang Shi,