Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique

Wang, Feifei and Liu, Yanjun and Yang, Erfu (2016) Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique. Circuits, Systems, and Signal Processing. pp. 1-19. ISSN 1531-5878 (https://doi.org/10.1007/s00034-015-0232-0)

[thumbnail of Wang-Liu-Yang-CSSP2016-Least-squares-based-iterative-identification-methods-for-linear-in-parameters]
Preview
 Text. Filename: Wang_Liu_Yang_CSSP2016_Least_squares_based_iterative_identification_methods_for_linear_in_parameters.pdf
Accepted Author Manuscript
Download (250kB)| Preview

Abstract

By extending the least squares-based iterative (LSI) method, this paper presents a decomposition-based LSI (D-LSI) algorithm for identifying linear-in-parameters systems and an interval-varying D-LSI algorithm for handling the identification problems of missing-data systems. The basic idea is to apply the hierarchical identification principle to decompose the original system into two fictitious sub-systems and then to derive new iterative algorithms to estimate the parameters of each sub-system. Compared with the LSI algorithm and the interval-varying LSI algorithm, the decomposition-based iterative algorithms have less computational load. The numerical simulation results demonstrate that the proposed algorithms work quite well.

ORCID iDs

Wang, Feifei, Liu, Yanjun and Yang, Erfu ORCID logoORCID: https://orcid.org/0000-0003-1813-5950;
CORE (COnnecting REpositories)