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Adaptive neural tracking control of nonlinear time‐delay systems with disturbances
Author(s) -
Wang Min,
Chen Bing,
Zhang Siying
Publication year - 2009
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.1082
Subject(s) - backstepping , control theory (sociology) , artificial neural network , nonlinear system , tracking error , adaptive control , tracking (education) , controller (irrigation) , computer science , radial basis function , scheme (mathematics) , lyapunov function , adaptive system , mathematics , control (management) , artificial intelligence , psychology , mathematical analysis , pedagogy , physics , quantum mechanics , agronomy , biology
In this paper, a novel adaptive neural tracking control scheme is presented for a class of perturbed strict‐feedback nonlinear time‐delay systems with unknown virtual control coefficients. The introduction of new estimated parameters reduces the number of adaptive parameters and the size of neural networks required. Based on radial basis function neural network on‐line approximation, an adaptive neural tracking controller is proposed by combining Lyapunov–Krasovskii functionals and decoupled backstepping. The proposed scheme guarantees semi‐global uniform ultimate boundedness of all the signals in the closed‐loop system and the tracking error converges to a small neighborhood around the origin. Simulation results demonstrate the effectiveness of the proposed results. Copyright © 2008 John Wiley & Sons, Ltd.