Publication detail

Artificial Neural Networks for On-Line Trained Controllers

PIVOŇKA, P.

Original Title

Artificial Neural Networks for On-Line Trained Controllers

Type

book chapter

Language

English

Original Abstract

This paper deals with the use of artificial neural networks employed as an on-line trained controller for a real process and simulation model control. Well-known back-propagation method is used as a learning algorithm intended to minimize the difference between the plant’s actual response and the desired reference signal. The influence of neural network’s parameters on a controlled plant output is discussed. We also attempted to find the rules of these parameters adjustment in view of the type of a transfer function in Laplace transform and tested the robustness of our controller burdened with the error signal. Some simulation and real process control results are also presented to evaluate the proposed design. Discussed in the last chapter are the possibilities of creating an adaptive neural controller.

Keywords

back-propagation, artificial neural nets, neural controller, adaptive neural controller

Authors

PIVOŇKA, P.

RIV year

2001

Released

7. 7. 2001

Publisher

Published by WSES Press, http://www.worldses.org

Location

http://www.worldses.org

ISBN

960-8052-39-4

Book

Advances in Systems Science: Measurement, Circuits and Control

Edition

Electrical and Computer Engineering Series - A series of Reference Books and Textbooks

Edition number

1

Pages from

189

Pages to

194

Pages count

6

BibTex

@inbook{BUT55021,
  author="Petr {Pivoňka}",
  title="Artificial Neural Networks for On-Line Trained Controllers",
  booktitle="Advances in Systems Science: Measurement, Circuits and Control",
  year="2001",
  publisher="Published by WSES Press, http://www.worldses.org",
  address="http://www.worldses.org",
  series="Electrical and Computer Engineering Series -
A series of Reference Books and Textbooks",
  edition="1",
  pages="6",
  isbn="960-8052-39-4"
}