Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises

Xing, Haoming and Ding, Feng and Zhang, Xiao and Luan, Xiaoli and Yang, Erfu (2024) Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises. Systems and Control Letters, 186. 105762. ISSN 0167-6911 (https://doi.org/10.1016/j.sysconle.2024.105762)

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Abstract

Multiple-input multiple-output (MIMO) systems have extensive applications in industrial processes and systems engineering. This letter applies the filtering identification idea to establish a filtered identification model and investigate a filtered auxiliary model-based recursive least squares (F-AM-RLS) algorithm for parameter identification of MIMO systems with colored noises. To improve the computational efficiency, this work further proposes a four-stage filtered auxiliary model-based recursive least squares (4S-F-AM-RLS) algorithm by means of the hierarchical identification principle. Then, by incorporating the forgetting factor, a four-stage filtered auxiliary model-based forgetting factor recursive least squares (4S-F-AM-FF-RLS) algorithm is given to improve the convergence speed and the estimation accuracy. Additionally, the computational complexity analysis of the proposed algorithms indicates that the 4S-F-AM-RLS algorithm effectively reduces the computational burden and improves computational efficiency. Finally, the effectiveness of the F-AM-RLS, 4S-F-AM-RLS and 4S-F-AM-FF-RLS algorithms is validated through a numerical example.

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