Novel identification algorithms for Hammerstein systems in ill-conditioned situations

Two algorithms named Recursive Least Square algorithm for Ill-Conditioned situations (RLS-IC) and Multi Innovation Stochastic Gradient algorithm for Ill-Conditioned situations (MISG-IC) are proposed based on multi-innovation identification theory, least squares, stochastic gradient and singular valu...

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Bibliographic Details
Published in:Systems science & control engineering 2021-01, Vol.9 (1), p.52-60
Main Authors: Nejati, A., Safarinejadian, B.
Format: Article
Language:English
Subjects:
Algorithms
Hammerstein systems
Innovations
insufficient excitation
Least squares
multi-innovation identification theory
Nonlinear systems
Parameter estimation
Singular value decomposition
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Summary:Two algorithms named Recursive Least Square algorithm for Ill-Conditioned situations (RLS-IC) and Multi Innovation Stochastic Gradient algorithm for Ill-Conditioned situations (MISG-IC) are proposed based on multi-innovation identification theory, least squares, stochastic gradient and singular value decomposition to identify Hammerstein systems in ill-conditioned situations. In ill-conditioned situations, identification algorithms based on classic least-squares and stochastic gradient lead to uncertain estimates and may be ineffective. Simulation examples show that the proposed algorithms are suitable for parameter estimation in Hammerstein nonlinear systems with ill-conditioned situations.
ISSN:2164-2583
2164-2583
DOI:10.1080/21642583.2020.1865214