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2005 | 15 | 3 | 369-381
Tytuł artykułu

Stabilising solutions to a class of nonlinear optimal state tracking problems using radial basis function networks

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A controller architecture for nonlinear systems described by Gaussian RBF neural networks is proposed. The controller is a stabilising solution to a class of nonlinear optimal state tracking problems and consists of a combination of a state feedback stabilising regulator and a feedforward neuro-controller. The state feedback stabilising regulator is computed on-line by transforming the tracking problem into a more manageable regulation one, which is solved within the framework of a nonlinear predictive control strategy with guaranteed stability. The feedforward neuro-controller has been designed using the concept of inverse mapping. The proposed control scheme is demonstrated on a simulated single-link robotic manipulator.
Rocznik
Tom
15
Numer
3
Strony
369-381
Opis fizyczny
Daty
wydano
2005
otrzymano
2004-11-06
poprawiono
2005-04-22
Twórcy
autor
  • Department of Electrical Engineering, University of Skikda, Al-Hadaik Rd., P.B.: 26, Skikda 21000, Algeria
  • Department of Electronics, Mentouri University, Zerzara, Ain-Bey Rd., Constantine 25000, Algeria
  • Department of Cybernetics, University of Reading, Whiteknights, Reading RG6 6AY, U.K.
Bibliografia
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  • Kambhampati C., Delgado A., Mason J.D. and Warwick K. (1997): Stable receding horizon control based on recurrent networks. - IEE Proc. Contr. Theory Applic., Vol. 144, No. 3, pp. 249-254.
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  • Michalska H. and Mayne D.Q. (1993): Robust receding horizon control of constrained nonlinear systems. - IEEE Trans. Automat. Contr., Vol. 38, No. 11, pp. 1623-1633.
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv15i3p369bwm
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