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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.

  • Web Address
  • DOI
  • Date of creation in the UzSCI system 07-12-2023
  • Read count 83
  • Date of publication 23-10-2023
  • Main LanguageIngliz
  • Pages111-122
English

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.

№ Author name position Name of organisation
1 Abdishukurov S.M. student TDTU
2 Sevinov J.U. dotsent TDTU
3 Boborayimov O.K. teacher TDTU
№ Name of reference
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