Publication detail

Generalized Predictive Control with Adaptive Model Based on Neural Networks

Petr Pivoňka, Petr Nepevný

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

journal article

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 it’s 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 it’s advantages and disadvantages are shown.

Keywords

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

RIV year

2005

Released

15.05.2005

ISBN

1109-2734

Pages from

385

Pages to

389

Pages count

5

BibTex


@article{BUT46530,
  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 it’s advantages and disadvantages are shown.",
  chapter="46530",
  journal="WSEAS Transactions on Circuits",
  number="4",
  volume="4",
  year="2005",
  month="may",
  pages="385",
  type="journal article"
}