Publication detail

Adaptive Constrained Generalized Predictive Control Based on Neural Network

NEPEVNÝ, P.

Original Title

Adaptive Constrained Generalized Predictive Control Based on Neural Network

Type

conference paper

Language

English

Original Abstract

This paper presents solution of constrained Generalized Predictive Control (GPC) with autoregressive model based on neural network. Neural model is able to observe system changes and adapt itself. Algorithm was implemented in MATLAB-Simulink with aspect of future implementation to Programmable Logic Controller (PLC) B&R. The usage possibilities of this approach were tested on mathematical and physical models in soft-real-time realization. Constrained GPC algorithm was compared with classical PSD controller and advantages and disadvantages of predictive control are shown.

Keywords

predictive, MPC, GPC, neural network, adaptive

Authors

NEPEVNÝ, P.

RIV year

2005

Released

1. 1. 2005

Publisher

Ing. Zdeněk Novotný CSc., Ondráčkova 105 Brno

Location

Brno

ISBN

80-214-2889-9

Book

Proceedings of the 11th conference student EEICT 2005

Pages from

51

Pages to

55

Pages count

5

BibTex

@inproceedings{BUT16289,
  author="Petr {Nepevný}",
  title="Adaptive Constrained Generalized Predictive Control Based on Neural Network",
  booktitle="Proceedings of the 11th conference student EEICT 2005",
  year="2005",
  pages="5",
  publisher="Ing. Zdeněk Novotný CSc., Ondráčkova 105 Brno",
  address="Brno",
  isbn="80-214-2889-9"
}