Publication detail
Generalized Predictive Control with Adaptive Model Based on Neural Networks
PIVOŇKA, P. NEPEVNÝ, P.
Original Title
Generalized Predictive Control with Adaptive Model Based on Neural Networks
English Title
Generalized Predictive Control with Adaptive Model Based on Neural Networks
Type
conference paper
Language
en
Original Abstract
Generalized Predictive Control (GPC) is well known control algorithm. If we put together predictive strategy of GPC and Neural Networks model, which is adaptive, then we obtain new controller with many advantages. Neural model is able to observe system changes and adapt itself, therefore regulator based on this model is adaptive. Algorithm was implemented in MATLAB-Simulink with aspect of future implementation to Programmable Logic Controller (PLC) B&R. It was tested on mathematical and physical models in soft-real-time realization. Predictive controller in comparison with classical discrete PID controller and its advantages and disadvantages are shown.
English abstract
Generalized Predictive Control (GPC) is well known control algorithm. If we put together predictive strategy of GPC and Neural Networks model, which is adaptive, then we obtain new controller with many advantages. Neural model is able to observe system changes and adapt itself, therefore regulator based on this model is adaptive. Algorithm was implemented in MATLAB-Simulink with aspect of future implementation to Programmable Logic Controller (PLC) B&R. It was tested on mathematical and physical models in soft-real-time realization. Predictive controller in comparison with classical discrete PID controller and its advantages and disadvantages are shown.
Keywords
GPC, MPC, predictive, control, adaptive model, Neural Networks
RIV year
2005
Released
15.06.2005
Publisher
WSEAS
Location
Lisabon
ISBN
960-8457-24-6
Book
Proceedings of the WSEAS Conferences NN'05, FS'05, EC'05
Pages from
1
Pages to
5
Pages count
5
Documents
BibTex
@inproceedings{BUT14827,
author="Petr {Pivoňka} and Petr {Nepevný}",
title="Generalized Predictive Control with Adaptive Model Based on Neural Networks",
annote="Generalized Predictive Control (GPC) is well known control algorithm. If we put together predictive strategy of GPC and Neural Networks model, which is adaptive, then we obtain new controller with many advantages. Neural model is able to observe system changes and adapt itself, therefore regulator based on this model is adaptive. Algorithm was implemented in MATLAB-Simulink with aspect of future implementation to Programmable Logic Controller (PLC) B&R. It was tested on mathematical and physical models in soft-real-time realization. Predictive controller in comparison with classical discrete PID controller and its advantages and disadvantages are shown.",
address="WSEAS",
booktitle="Proceedings of the WSEAS Conferences NN'05, FS'05, EC'05",
chapter="14827",
institution="WSEAS",
year="2005",
month="june",
pages="1--5",
publisher="WSEAS",
type="conference paper"
}