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Adaptive robust NN control of nonlinear systems
Wen G.-X.2; Liu Y.-J.2; Chen C.L.P.1
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6676 LNCS
IssuePART 2
AbstractA direct adaptive neural networks (NNs) control based on the backstepping technique is proposed for uncertain nonlinear discrete-time systems in the strict-feedback form. The NNs are utilized to approximate unknown functions, and a stable adaptive neural backstepping controller is synthesized. The fact that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) is proven so that it is clear that the tracking error converges to a small neighborhood of zero by choosing the design parameters appropriately. Compared with the previous research for discrete-time systems, the proposed algorithm improves the robustness of the closed-loop system. Therefore, it ensures the feasibility of the control method. © 2011 Springer-Verlag.
Keywordadaptive robust control Neural networks nonlinear systems
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Document TypeConference paper
Affiliation1.Universidade de Macau
2.Liaoning University of Technology
Recommended Citation
GB/T 7714
Wen G.-X.,Liu Y.-J.,Chen C.L.P.. Adaptive robust NN control of nonlinear systems[C],2011:535-541.
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