Neural based adaptive control of a class of dynamical nonlinear processes

Authors:
Emil Petre;Dan Selisteanu;Dorin Sendrescu
Affiliations:
Department of Automatic Control, University of Craiova, Craiova, Romania;Department of Automatic Control, University of Craiova, Craiova, Romania;Department of Automatic Control, University of Craiova, Craiova, Romania
Venue:
ICAI'06 Proceedings of the 7th WSEAS International Conference on Automation & Information
Year:
2006

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Abstract

A nonlinear adaptive controller for a class of nonlinear plants with incompletely known and time varying dynamics is presented. It is based on a recurrent neural network used as a dynamical model of the plant. The adaptive controller design is realized by using an input-output feedback linearizing technique. The model parameters, that is the controller parameters are updated on-line such that the behaviour of closed loop system is closely to those of a linear system. A local convergence of the algorithm is provided for the case of constant reference output. Computer simulations are included to illustrate the performances of the proposed controller.