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Nepevný, P., Pivoňka, P.
Original Title
Hot-Air Tunel Control Using Multi-Dimensional Predictive Controller Based on Neural Network Model
English Title
Type
Paper in proceedings (conference paper)
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.
English abstract
Keywords
MPC, prediction, neural network, control, multidimensional control
Key words in English
Authors
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 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" }