Multi-innovation recursive identification methods for nonlinear sandwich systems using the auxiliary model

In this paper, an auxiliary model-based multi-innovation least squares algorithm is used to solve the identification problem existing in the nonlinear sandwich system. Nonlinear sandwich systems are widely used in real industrial systems, and effective system identification is beneficial for designi...

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Vydané v:Applied mathematical modelling Ročník 150; s. 116398
Hlavní autori: Liu, Qinyao, Dong, Qi, Jiang, Haolong, Chen, Feiyan, Wang, Xuchen
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Inc 01.02.2026
Predmet:
Auxiliary model
Heat exchanger
Multi-innovation theory
Nonlinear sandwich systems
Parameter estimation
Recursive least squares
Multi-innovation theory
Parameter estimation
Auxiliary model
Nonlinear sandwich systems
Recursive least squares
Heat exchanger
ISSN:0307-904X
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Popis
Shrnutí:In this paper, an auxiliary model-based multi-innovation least squares algorithm is used to solve the identification problem existing in the nonlinear sandwich system. Nonlinear sandwich systems are widely used in real industrial systems, and effective system identification is beneficial for designing effective controllers to control them. The nonlinear sandwich system consists of two linear modules and one nonlinear module in which there are unmeasurable internal variables. To solve the problem, an auxiliary model is constructed in this paper to replace the unmeasurable variables with their outputs. Then the multi-innovation theory is introduced to improve the accuracy of the algorithm and the convergence of the algorithm is proved. Finally, a numerical example and one physical simulation example are used to prove the effectiveness of the algorithm proposed in this paper. •An auxiliary model is built to solve the inner parameter estimation problem.•Multi-innovation theory is used to improve the accuracy of identification results.•The convergence of the proposed algorithm is proved.•Two examples are used to prove the effectiveness of the algorithm.
ISSN:0307-904X
DOI:10.1016/j.apm.2025.116398