Detail publikace

Hot-Air Tunel Control Using Multi-Dimensional Predictive Controller Based on Neural Network Model

Nepevný, P., Pivoňka, P.

Originální název

Hot-Air Tunel Control Using Multi-Dimensional Predictive Controller Based on Neural Network Model

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper presents using of a multi-dimensional model predictive controller for hot-air tunnel control. Two quantities of hot-air tunnel are controlled – the air flow and the temperature. Mode predictive controller is a kind of optimal controller based on model. Model predicts future system output, which is used for finding an optimal control action. We used a feed-forward neural network model with backpropagation learning algorithm. Obtained controller is adaptive, because the neural network model is able to observe system changes and adapt itself. The algorithm was implemented in MATLAB-Simulink and tested on a physical model. Communication between PC and hot-air tunnel was provided by PLC (connected via Ethernet.

Klíčová slova

MPC, prediction, neural network, control, multidimensional control

Autoři

Nepevný, P., Pivoňka, P.

Rok RIV

2006

Vydáno

12. 11. 2006

Nakladatel

DAAAM International Vienna

Místo

Vídeň

ISBN

3-901509-57-7

Kniha

Anals of DAAAM for 2006 & Proceedings

Strany od

267

Strany do

268

Strany počet

2

BibTex

@inproceedings{BUT24156,
  author="Petr {Nepevný} and Petr {Pivoňka}",
  title="Hot-Air Tunel Control Using Multi-Dimensional Predictive Controller Based on Neural Network Model",
  booktitle="Anals of DAAAM for 2006 & Proceedings",
  year="2006",
  pages="2",
  publisher="DAAAM International Vienna",
  address="Vídeň",
  isbn="3-901509-57-7"
}