Detail publikace

Simple Neural Network-Based Adaptive Controller for Heating System

Originální název

Simple Neural Network-Based Adaptive Controller for Heating System

Anglický název

Simple Neural Network-Based Adaptive Controller for Heating System

Jazyk

en

Originální abstrakt

The algorithm for the semi-inversion controller has been designed for adaptive control based on neural networks. This controller originally designed for linear systems proved to have favorable characteristics also for considerably non-linear systems. The algorithm deals with extreme inversion controlling actions occurring in inversion control. We used the semi-inversion controller for control a real system – laboratory hot-air system model. The efficient of control algorithm we demonstrate by control MIMO system with 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.

Anglický abstrakt

The algorithm for the semi-inversion controller has been designed for adaptive control based on neural networks. This controller originally designed for linear systems proved to have favorable characteristics also for considerably non-linear systems. The algorithm deals with extreme inversion controlling actions occurring in inversion control. We used the semi-inversion controller for control a real system – laboratory hot-air system model. The efficient of control algorithm we demonstrate by control MIMO system with 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.

BibTex


@inproceedings{BUT11409,
  author="Petr {Pivoňka} and Václav {Veleba}",
  title="Simple Neural Network-Based Adaptive Controller for Heating System",
  annote="The algorithm for the semi-inversion controller has been designed for adaptive control based on neural networks. This controller originally designed for linear systems proved to have favorable characteristics also for considerably non-linear systems. The algorithm deals with extreme inversion controlling actions occurring in inversion control. We used the semi-inversion controller for control a real system – laboratory hot-air system model. The efficient of control algorithm we demonstrate by control MIMO system with 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.",
  address="Rektor der Hochschule Zitttau/Görlitz",
  booktitle="Proceedings East West Fuzzy Colloquium 2004",
  chapter="11409",
  institution="Rektor der Hochschule Zitttau/Görlitz",
  year="2004",
  month="september",
  pages="163",
  publisher="Rektor der Hochschule Zitttau/Görlitz",
  type="conference paper"
}