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Adaptive neural control for a class of uncertain nonlinear systems with unknown time delay
Author(s) -
Wang Dan,
Lan Weiyao
Publication year - 2008
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.1351
Subject(s) - control theory (sociology) , nonlinear system , artificial neural network , bounded function , adaptive control , feed forward , controller (irrigation) , singularity , computer science , function (biology) , class (philosophy) , scheme (mathematics) , control (management) , mathematics , engineering , control engineering , artificial intelligence , mathematical analysis , agronomy , physics , quantum mechanics , evolutionary biology , biology
A neural network (NN)‐based robust adaptive control design scheme is developed for a class of nonlinear systems represented by input–output models with an unknown nonlinear function and unknown time delay. By approximating on‐line the unknown nonlinear functions with a three‐layer feedforward NN, the proposed approach does not require the unknown parameters to satisfy the linear dependence condition. The control law is delay independent and possible controller singularity problem is avoided. It is proved that with the proposed neural control law, all the signals in the closed‐loop system are semiglobally bounded in the presence of unknown time delay and unknown nonlinearity. A simulation example is presented to demonstrate the method. Copyright © 2008 John Wiley & Sons, Ltd.