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Adaptive Dynamic Surface Control with Guaranteed L ∞ Tracking Performance for a Class of Uncertain Nonlinear Systems with Unknown Time Delays
Author(s) -
Qu Weiran,
Lin Yan,
Zhao Qichao
Publication year - 2014
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.747
Subject(s) - initialization , control theory (sociology) , nonlinear system , artificial neural network , tracking error , surface (topology) , class (philosophy) , scheme (mathematics) , computer science , tracking (education) , adaptive control , control (management) , mathematics , mathematical optimization , artificial intelligence , psychology , pedagogy , physics , geometry , quantum mechanics , programming language , mathematical analysis
This paper is aimed at exploring dynamic surface control ( DSC ) for a class of uncertain nonlinear systems in strict‐feedback form with time delays. Combining the F inite C overing L emma ( H eine‐ B orel T heorem) with neural networks, a novel method is proposed to approximate time delay terms, which leads to the abandonment of traditional L yapunov‐ K rasovskii functionals. Then, a surface error modification and an initialization technique are proposed to guarantee theℒ ∞tracking performance. Moreover, by applying a newly‐developed neural network based adaptive control technique, it is shown that the update law for the proposed DSC scheme is needed only at the last design step with only one parameter being estimated online, which significantly reduces the computational burden, compared with current DSC schemes. Simulation results are presented to illustrate the efficiency of the proposed scheme.