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Application of Neuro-Controller Models for Adaptive Control

  • Viktor Smorodin
  • Vladislav Prokhorenko
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 836)

Abstract

In this paper, a method for constructing a model of a controller based on recurrent neural network architecture for implementation of control for the optimal trajectory finding problem is considered. A type of a neuro-controller based on recurrent neural network architecture with long short-term memory blocks as a knowledge base on the external environment and previous states of the controller is proposed. The formalization of the technological cycle of a special type for adaptive control of a production process using the model of the neuro-controller is given.

Keywords

Artificial neural networks Recurrent neural networks Neuro-controller Knowledge base Artificial intelligence Mathematical models Control system Adaptive control 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Francisk Skorina Gomel State UniversityGomelBelarus

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