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Adaptive control of a class of nonlinear systems using multiple models with smooth controller
Author(s) -
Chen Wei,
Sun Jian,
Chen Chen,
Chen Jie
Publication year - 2015
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.3113
Subject(s) - control theory (sociology) , scheme (mathematics) , nonlinear system , controller (irrigation) , identification scheme , dimension (graph theory) , computer science , identification (biology) , transient (computer programming) , adaptive control , class (philosophy) , convex combination , regular polygon , system identification , convex optimization , control (management) , mathematics , artificial intelligence , data modeling , mathematical analysis , physics , botany , geometry , quantum mechanics , database , pure mathematics , agronomy , biology , operating system , process (computing)
Summary The idea of using multiple models to improve transient performance in adaptive control systems with large uncertainty or time varying parameters was introduced in 1990s. However, the commonly used scheme with switching has some potential drawbacks. In this paper, a new multiple model scheme is proposed for strict‐feedback nonlinear systems. In order to avoid the possible chattering resulted from the controller's switching, a continuous controller based on the convex combination of parameter estimates of identification models is presented, which ensures the better use of the information of identification models than the switching scheme. Also, the number of necessary models is just one more than the dimension of the unknown system parameter, which is more practical. Simulation studies are presented to demonstrate the efficiency of the proposed scheme. Copyright © 2013 John Wiley & Sons, Ltd.