Přístupnostní navigace
E-application
Search Search Close
Publication detail
Hynek Vychodil, Michal Schmidt, Petr Nepevný,Petr Pivoňka
Original Title
Generalized Predictive Control with a Non-linear Autoregressive Model
Type
journal article - other
Language
English
Original Abstract
This paper presents a solution to computation of predictive control using non-linear auto-regressive models. For the non-linear model a neural network is used as a perspective tool for modelling of dynamic systems. However, the described approach is applicable to any type of auto-regressive model. The model is not linearized in the operating point, but in each control optimization step the model’s derivative is computed (linearization) for all points in the prediction horizon. The method can be used in real-time control. This is verified by porting the algorithm directly to the PLC.
Key words in English
Neural network, Non-linear Modelling, Predictive control
Authors
RIV year
2005
Released
30. 3. 2005
ISBN
1109-2734
Periodical
WSEAS Transactions on Circuits
Year of study
Number
3
State
Hellenic Republic
Pages from
125
Pages to
130
Pages count
6
BibTex
@article{BUT46302, author="Hynek {Vychodil} and Michal {Schmidt} and Petr {Nepevný} and Petr {Pivoňka}", title="Generalized Predictive Control with a Non-linear Autoregressive Model", journal="WSEAS Transactions on Circuits", year="2005", volume="2005", number="3", pages="6", issn="1109-2734" }