A neural predictive controller for non-linear systems

M. Lazar, O. Pastravanu

Research output: Contribution to journalArticleAcademicpeer-review

54 Citations (Scopus)
3 Downloads (Pure)

Abstract

Design and implementation are studied for a neural network-based predictive controller meant to govern the dynamics of non-linear processes. The advantages of using neural networks for modeling non-linear processes are shown together with the construction of neural predictors. The resulting implementation of the neural predictive controller is able to eliminate the most significant obstacles encountered in non-linear predictive control applications by facilitating the development of non-linear models and providing a rapid, reliable solution to the control algorithm. Controller design and implementation are illustrated for a plant frequently referred to in the literature. Results are given for simulation experiments, which demonstrate the effectiveness of the proposed approach.
Original languageEnglish
Pages (from-to)315-324
Number of pages10
JournalMathematics and Computers in Simulation
Volume60
Issue number3-5
DOIs
Publication statusPublished - 2002

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