Recurrent Neural Networks in Linear Systems Controlling

P. C. PATIC¹, R. M. ZEMOURI R.², L. DUŢĂ¹
¹Valahia University of Târgovişte,
18-24, Unirii Ave., Târgovişte, Romania
patic@valahia.ro, duta@valahia.ro

²Laboratoire d’Automatique du CNAM,
21, Rue Pinel, 75013 Paris, France
ryad.zemouri@cnam.fr

Abstract: This paper presents an application of an ANN (Artificial Neural Network) of a RNRF type (Recurrent Network with Radial basis Function) in controlling a linear system. The performance of ANN-based control solution is compared with a classic controller and the results show that ANN behaves better than the classic controller. MATLAB simulation performed show that the coupling between the ANN and a proportional controller gives the best performance.

Keywords: Human-machine interface, usability criteria, end-user development, risks.

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CITE THIS PAPER AS:
P. C. PATIC, R. M. ZEMOURI R., L. DUŢĂ, Recurrent Neural Networks in Linear Systems Controlling, Studies in Informatics and Control, ISSN 1220-1766, vol. 19 (2), pp. 153-158, 2010.