Publication detail

ADAPTIVE CONTROL OF HOT-AIR LABORATORY MODEL USING ARTIFICIAL NEURAL NETWORKS

VELEBA, V.

Original Title

ADAPTIVE CONTROL OF HOT-AIR LABORATORY MODEL USING ARTIFICIAL NEURAL NETWORKS

Type

conference paper

Language

English

Original Abstract

The real application of the neural network as a control and estimation element was described. Two parameters can be controlled in a laboratory hot-air system – the airflow and the temperature inside the tunnel. The controlled system displays ordinary negative effects encountered in industrial applications. When the basic approaches to control using neural networks had been studied, a new control algorithm - semi-inversion controller was designed. The controller is capable of solving problems such as oscillating control action, noise sensitivity and ill-estimated parameters in the initial phase of control or adjustment.

Keywords

Neural Network, Adaptive Control, Semiinversion Controller

Authors

VELEBA, V.

RIV year

2004

Released

1. 1. 2004

Publisher

Ing. Zdeněk Novotný CSc.

Location

Brno

ISBN

80-214-2636-5

Book

Proceedings of 10th Conference Student EEICT 2004

Edition number

první

Pages from

407

Pages to

411

Pages count

5

URL

http://www.feec.vutbr.cz/EEICT/

BibTex

@inproceedings{BUT11373,
  author="Václav {Veleba}",
  title="ADAPTIVE CONTROL OF HOT-AIR LABORATORY MODEL USING ARTIFICIAL NEURAL NETWORKS",
  booktitle="Proceedings of 10th Conference Student EEICT 2004",
  year="2004",
  number="první",
  pages="5",
  publisher="Ing. Zdeněk Novotný CSc.",
  address="Brno",
  isbn="80-214-2636-5",
  url="http://www.feec.vutbr.cz/EEICT/"
}