Přístupnostní navigace
E-application
Search Search Close
Publication result detail
PIVOŇKA, P., VELEBA, V.
Original Title
Application of Neural Networks for Hot-Air System Control
English Title
Type
Peer-reviewed article not indexed in WoS or Scopus
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.
English abstract
Key words in English
Semi-inversion controller, hot-air system, noise rejection, programmable logic controller, PID
Authors
Released
25.03.2004
ISBN
1109-2777
Periodical
WSEAS Transactions on Systems
Volume
3
Number
2
State
United States of America
Pages from
757
Pages count
4
BibTex
@article{BUT41840, author="Petr {Pivoňka} and Václav {Veleba}", title="Application of Neural Networks for Hot-Air System Control", journal="WSEAS Transactions on Systems", year="2004", volume="3", number="2", pages="4", issn="1109-2777" }