ALGORITHMS FOR SYNTHESIS OF ADAPTIVE CONTROL SYSTEMS  BASED ON THE NEURAL NETWORK APPROACH

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ALGORITHMS FOR SYNTHESIS OF ADAPTIVE CONTROL SYSTEMS BASED ON THE NEURAL NETWORK APPROACH

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Here is algorithms for the synthesis of adaptive control systems based on the neural network approach presented. The issues of choice of architectures of neural networks that produce parametric identification of the object regulation. Adaptation neural networks that reproduce the optimal parameters of implemented controllers, methods of forming training samples for their training are considered. The another question for using the theory of artificial neural networks for approximating the functional of the controller's tuning parameters are determined. Structures of synthesized neural networks of parametric identification for objects with self-alignment in an open loop ACS are proposed. Algorithms made it possible to effectively solve the problems of adaptive systems synthesis based on the neural network approach in control systems of technological processes.

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# control object# parametric identification# adaptive control system# artificial neural network# neural network learning

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https://eroi.uz/11.0008/A1223-0009

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