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

Type

conference paper

Language

English

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.

Keywords

GPC, MPC, predictive, control, adaptive model, Neural Networks

Authors

PIVOŇKA, P.; NEPEVNÝ, P.

RIV year

2005

Released

15. 6. 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

BibTex

@inproceedings{BUT14827,
  author="Petr {Pivoňka} and Petr {Nepevný}",
  title="Generalized Predictive Control with Adaptive Model Based on Neural Networks",
  booktitle="Proceedings of the WSEAS Conferences NN'05, FS'05, EC'05",
  year="2005",
  pages="1--5",
  publisher="WSEAS",
  address="Lisabon",
  isbn="960-8457-24-6"
}