Publication detail

Application of Neural Networks for Hot-Air System Control

VELEBA, V.

Original Title

Application of Neural Networks for Hot-Air System Control

Type

conference paper

Language

English

Original Abstract

Application of an adaptive semi-inversion neural controller for a laboratory hot-air system model is described. The system can be used to control two parameters – the airflow and the temperature inside the tunnel. The hot-air system displays negative effects commonly occurring in industrial applications – different static amplifications at different operating points, large offset increasing with time, dead zone and noise. The used semi-inversion neural controller is based on an inversion controller, but is capable of solving problems such as oscillating control action, noise sensitivity and ill-estimated parameters in the initial phase of control or adjustment.

Key words in English

Semi-inversion controller, hot-air system, noise rejection, programmable logic controller, PID

Authors

VELEBA, V.

RIV year

2004

Released

26. 3. 2004

Publisher

WSEAS

Location

Udine, Itálie

ISBN

960-8052-96-3

Book

Proceedings of the WSEAS International Conferences NNA'04

Pages from

1

Pages to

4

Pages count

4

BibTex

@inproceedings{BUT11264,
  author="Václav {Veleba}",
  title="Application of Neural Networks for Hot-Air System Control",
  booktitle="Proceedings of the WSEAS International Conferences NNA'04",
  year="2004",
  pages="4",
  publisher="WSEAS",
  address="Udine, Itálie",
  isbn="960-8052-96-3"
}