Journal
MATHEMATICS
Volume 7, Issue 7, Pages -Publisher
MDPI
DOI: 10.3390/math7070609
Keywords
least-squares; iterative identification; hierarchical; parameter estimation; multivariable system
Categories
Funding
- National Natural Science Foundation of China [61304093]
- Natural Science Foundation of Shandong Province [ZR201702170236]
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This paper is concerned with the identification problem for multivariable equation-error systems whose disturbance is an autoregressive moving average process. By means of the hierarchical identification principle and the iterative search, a hierarchical least-squares-based iterative (HLSI) identification algorithm is derived and a least-squares-based iterative (LSI) identification algorithm is given for comparison. Furthermore, a hierarchical multi-innovation least-squares-based iterative (HMILSI) identification algorithm is proposed using the multi-innovation theory. Compared with the LSI algorithm, the HLSI algorithm has smaller computational burden and can give more accurate parameter estimates and the HMILSI algorithm can track time-varying parameters. Finally, a simulation example is provided to verify the effectiveness of the proposed algorithms.
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