Recursive identification of Hammerstein systems with dead-zone input nonlinearity

A robust recursive identification algorithm is proposed for Hammerstein systems with dead-zone input nonlinearity and unknown dynamic disturbances. The dynamic disturbance is considered as a slow time-varying parameter to be estimated by the recursive forgetting tracking estimation technique. Based...

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Vydané v:Chinese Control and Decision Conference s. 4050 - 4055
Hlavní autori: Dong, Shijian, Yu, Li, Zhang, Wen-An, Yang, Xusheng
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.06.2019
Predmet:
Conferences
convergence
dead-zone input nonlinearity
disturbances
Hammerstein systems
recursive least squares
ISSN:1948-9447
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Abstract A robust recursive identification algorithm is proposed for Hammerstein systems with dead-zone input nonlinearity and unknown dynamic disturbances. The dynamic disturbance is considered as a slow time-varying parameter to be estimated by the recursive forgetting tracking estimation technique. Based on the decoupling estimation theory and overparameterized method, two improved recursive least squares algorithms are constructed to estimate the model parameters and disturbance sequence. The variable forgetting factor strategy is also used to improve the tracking estimation performance of the disturbance and the estimation accuracy of the model parameters. Besides, the asymptotic convergence property of the proposed algorithm is also illustrated in detail. One example is used to demonstrate the superiority of the proposed algorithm.
AbstractList A robust recursive identification algorithm is proposed for Hammerstein systems with dead-zone input nonlinearity and unknown dynamic disturbances. The dynamic disturbance is considered as a slow time-varying parameter to be estimated by the recursive forgetting tracking estimation technique. Based on the decoupling estimation theory and overparameterized method, two improved recursive least squares algorithms are constructed to estimate the model parameters and disturbance sequence. The variable forgetting factor strategy is also used to improve the tracking estimation performance of the disturbance and the estimation accuracy of the model parameters. Besides, the asymptotic convergence property of the proposed algorithm is also illustrated in detail. One example is used to demonstrate the superiority of the proposed algorithm.
Author Yang, Xusheng
Yu, Li
Dong, Shijian
Zhang, Wen-An
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  organization: Department of Automation, Zhejiang University of Technology and Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, 310023, PR China
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Snippet A robust recursive identification algorithm is proposed for Hammerstein systems with dead-zone input nonlinearity and unknown dynamic disturbances. The dynamic...
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StartPage 4050
SubjectTerms Conferences
convergence
dead-zone input nonlinearity
disturbances
Hammerstein systems
recursive least squares
Title Recursive identification of Hammerstein systems with dead-zone input nonlinearity
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