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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v47.i12.20
pages 18-28

Predictive Control of Nonlinear Objects Using Evolving Feedforward Neural Networks

Oleg G. Rudenko
Kharkov National University of Radio and Electronics, Kharkov
Alexander A. Bezsonov
Kharkov National University of Radio and Electronics, Kharkov

SINOPSIS

The development of a method of nonlinear objects control with the evolving feedforward neural networks is considered. The neural networks are used to build a nonlinear model of the object which is then utilized for recursive prediction of the object behavior in the model predictive control system. Genetic algorithms used for the neural network training significantly speed up the training process. The simulation results confirm the effectiveness of the proposed control method.


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