Publication detail

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

Nepevný, P., Pivoňka, P.

Original Title

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

Type

conference paper

Language

English

Original Abstract

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.

Keywords

MPC, prediction, neural network, control, multidimensional control

Authors

Nepevný, P., Pivoňka, P.

RIV year

2006

Released

12. 11. 2006

Publisher

DAAAM International Vienna

Location

Vídeň

ISBN

3-901509-57-7

Book

Anals of DAAAM for 2006 & Proceedings

Pages from

267

Pages to

268

Pages count

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"
}