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Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

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

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v36.i9.20
13 pages

Adaptive Control of Nonlinear Objects Using CMAC Neural Network

Oleg G. Rudenko
Kharkov National University of Radio and Electronics, Kharkov
Alexander A. Bessonov
Kharkov National University of Radioelectronics, Kharkov, Ukraine


Neural network strategies of indirect adaptive control of unknown nonlinear dynamic objects are suggested. The studied objects are described by NARMA-models and for their identification and control the CMAC network is used. Efficiency of use of CMAC neural network for control of nonlinear stationary and nonstationary objects is demonstrated by simulation modeling.

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