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A robust adaptive control method for Wiener nonlinear systems
Author(s) -
Zhang Bi,
Mao Zhizhong
Publication year - 2016
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3580
Subject(s) - control theory (sociology) , nonlinear system , adaptive control , noise (video) , block (permutation group theory) , wiener process , dead zone , inverse , stability (learning theory) , computer science , mathematics , robust control , mathematical optimization , control (management) , artificial intelligence , physics , oceanography , geometry , quantum mechanics , machine learning , image (mathematics) , geology
Summary This paper proposes a new robust adaptive control method for Wiener nonlinear systems with uncertain parameters. The considered Wiener systems are different from the previous ones in the sense that we consider nonlinear block approximation error, process noise, and measurement noise. The parameterization model is obtained based on the inverse of the nonlinear function block. The adaptive control method is derived from a modified criterion function that can overcome non‐minimum phase property of the linear subsystem. The parameter adaptation is performed by using a robust recursive least squares algorithm with a deadzone weighted factor. The control law compensates the model error by incorporating the unmodeled dynamics estimation. Theoretical analysis indicates that the closed‐loop system stability can be guaranteed under mild conditions. Numerical examples including an industrial problem are studied to validate the results. Copyright © 2016 John Wiley & Sons, Ltd.