Data filtering-based least squares iterative algorithm for Hammerstein nonlinear systems by using the model decomposition

Ma, Junxia and Ding, Feng and Yang, Erfu (2016) Data filtering-based least squares iterative algorithm for Hammerstein nonlinear systems by using the model decomposition. Nonlinear Dynamics, 83 (4). pp. 1895-1908. ISSN 0924-090X (https://doi.org/10.1007/s11071-015-2454-x)

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Abstract

This paper focuses on the iterative identification problems for a class of Hammerstein nonlinear systems. By decomposing the system into two fictitious subsystems, a decomposition-based least squares iterative algorithm is presented for estimating the parameter vector in each subsystem. Moreover, a data filtering-based decomposition least squares iterative algorithm is proposed. The simulation results indicate that the data filtering-based least squares iterative algorithm can generate more accurate parameter estimates than the least squares iterative algorithm.

ORCID iDs

Ma, Junxia, Ding, Feng ORCID logoORCID: https://orcid.org/0000-0002-9787-4171 and Yang, Erfu ORCID logoORCID: https://orcid.org/0000-0003-1813-5950;
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