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A novel adaptive control approach for nonlinearly parameterized systems
Author(s) -
Chen Zhiyong
Publication year - 2015
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2462
Subject(s) - parameterized complexity , bottleneck , adaptive control , control theory (sociology) , controller (irrigation) , computer science , simple (philosophy) , convergence (economics) , equivalence (formal languages) , stability (learning theory) , information bottleneck method , linear system , control (management) , mathematical optimization , mathematics , artificial intelligence , algorithm , machine learning , philosophy , epistemology , discrete mathematics , agronomy , economics , mutual information , biology , embedded system , economic growth , mathematical analysis
SUMMARY Nonlinearly parameterized systems are commonly encountered in control of practical systems. However, the conventional adaptive estimation and control strategies, based on the essential assumption of linear parameterization, are incapable of dealing with this class of systems. This incapability in turn becomes a bottleneck for prevalent applications of adaptive control. In literature, there have been some attempts to break through this bottleneck by investigating the characteristics of nonlinearities. However, it is still open for an implementable strategy that is powerful for nonlinearly parameterized systems as the certainty equivalence principle for linearly parameterized systems. This paper aims to contribute an attempt to this open problem by proposing a novel adaptive control approach. On the one hand, the controller is conceptually simple, and it does not explicitly rely on the expression of system nonlinearities. On the other hand, the controller is able to achieve system stability and parameter convergence. Copyright © 2013 John Wiley & Sons, Ltd.