Hybrid adaptive control based on a Hopfield dynamic neural network for nonlinear dynamical systems

I. Hsum Li, Lian Wang Lee, Wei Yen Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a hybrid adaptive control scheme based on Hopfield-based dynamic neural network (HACHNN) for SISO nonlinear systems. An auxiliary direct adaptive controller is proposed to ensure the stability in the time-interval of when an indirect adaptive controller is failed because of ĝ(x)→0. The weights of the Hopfield-based dynamic neural network are on-line tuned by the adaptive laws derived in the sense of Lyapunov theorem, so that the stability of the closed-loop system can be guaranteed, and all signals in the closed-loop system are bounded. The designed structure of the Hopfield-based dynamic neural network maintains the tracking performance of the control scheme, and it also makes the practical implementation much easier.

Original languageEnglish
Title of host publication2012 International Joint Conference on Neural Networks, IJCNN 2012
DOIs
Publication statusPublished - 2012 Aug 22
Event2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, Australia
Duration: 2012 Jun 102012 Jun 15

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Other

Other2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
CountryAustralia
CityBrisbane, QLD
Period12/6/1012/6/15

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Keywords

  • Hopfield dynamic neural network
  • hybrid adaptive control scheme

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Li, I. H., Lee, L. W., & Wang, W. Y. (2012). Hybrid adaptive control based on a Hopfield dynamic neural network for nonlinear dynamical systems. In 2012 International Joint Conference on Neural Networks, IJCNN 2012 [6252454] (Proceedings of the International Joint Conference on Neural Networks). https://doi.org/10.1109/IJCNN.2012.6252454