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Identification of Dynamical System’s Parameters Using Neural Networks

EasyChair Preprint no. 7173

6 pagesDate: December 7, 2021


The article shows that neural networks can be effectively used to identify the parameters of dynamic systems. The main attention in the paper is paid to modelling and practical results obtained in the MATLAB Neural Network Toolbox environment. The use of the feedforward network and the Elman recurrent network is discussed. The simulation results show that the identification of dynamic systems using neural networks is most effective when the experimental data on the system contains internal redundancy or are incomplete.

Keyphrases: activation function, computational error, control system, Dynamical System’s Parameters, Elman's Recurrent Network, feedforward network, MATLAB Neural Network Toolbox, neural networks, plant identification panel, SLE

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Nataliia Shybytska},
  title = {Identification of Dynamical System’s Parameters  Using Neural Networks},
  howpublished = {EasyChair Preprint no. 7173},

  year = {EasyChair, 2021}}
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