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Least Squares Identification for Hammerstein Multi-input Multi-output Systems Based on the Key-Term Separation Technique

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Abstract

System modeling and parameter estimation are basic for system analysis and controller design. This paper considers the parameter identification problem of a Hammerstein multi-input multi-output (H-MIMO) system. In order to avoid the product terms in the identification model, we derive a pseudo-linear identification model of the H-MIMO system through separating a key term from the output equation of the system and present a hierarchical generalized least squares (LS) algorithm for estimating the parameters of the system. Moreover, we present a new LS algorithm to reduce the computational burden. The proposed algorithms are simple in principle and can achieve a higher computational efficiency than the over-parameterization-based LS estimation algorithm. Finally, we test the proposed algorithms by the simulation example and show their effectiveness.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61273194), the Research Innovation Program for College Graduates of Jiangsu Province (No. KYLX\(\_1121\)) and the PAPD of Jiangsu Higher Education Institutions.

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Authors and Affiliations

  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214122, People’s Republic of China

    Qianyan Shen & Feng Ding

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  1. Qianyan Shen
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  2. Feng Ding
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Correspondence to Feng Ding.

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Shen, Q., Ding, F. Least Squares Identification for Hammerstein Multi-input Multi-output Systems Based on the Key-Term Separation Technique. Circuits Syst Signal Process 35, 3745–3758 (2016). https://doi.org/10.1007/s00034-015-0211-5

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