Artificial intelligence

Scientific journal

ISSN 2710-1673

ONLINE: ISSN 2710-1681

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Training of Neuroemulators with Use of Pseudoregularization for Model Reference Adaptive Neurocontrol

Chernodub A.1
1 Institute of Mathematical Machines and Systems Problems of NAS of Ukraine

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UDC: 681.513.7
Publication Language: Russian
Stuc. intelekt. 2012; 17(4):602-614

Abstract: The problems of identification and control for nonlinear dynamic object with use of neural networks are considered. The Extended Kalman Filter method for neural networks training is described. Pseudoregularization method for effective training of neuroemulator for Model Reference Adaptive Neurocontrol is proposed. The results of numerical experiments for training of neuroemulators and neurocontrollers are presented.

Keywords: neurocontrol, the extended Kalman filter, pseudoregularization

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