Detail publikace

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

VELEBA, V.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Neural Network, Adaptive Control, Semiinversion Controller

Autoři

VELEBA, V.

Rok RIV

2004

Vydáno

1. 1. 2004

Nakladatel

Ing. Zdeněk Novotný CSc.

Místo

Brno

ISBN

80-214-2636-5

Kniha

Proceedings of 10th Conference Student EEICT 2004

Číslo edice

první

Strany od

407

Strany do

411

Strany počet

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/"
}