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Description
  • Článek se zabývá možnostmi použití neuronových sítí v prediktivních řídicích algoritmech. (cs)
  • 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 usedd in real-time control. This is verified by porting the algorithm directly to the PLC.
  • 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 usedd in real-time control. This is verified by porting the algorithm directly to the PLC. (en)
Title
  • Generalized Predictive Control with a Non-linear Autoregressive Model
  • Generalized Predictive Control with a Non-linear Autoregressive Model (en)
  • Prediktivní řízení s nelineárním autoregresivním modelem. (cs)
skos:prefLabel
  • Generalized Predictive Control with a Non-linear Autoregressive Model
  • Generalized Predictive Control with a Non-linear Autoregressive Model (en)
  • Prediktivní řízení s nelineárním autoregresivním modelem. (cs)
skos:notation
  • RIV/00216305:26220/05:PU50363!RIV06-MSM-26220___
http://linked.open.../vavai/riv/strany
  • 125-130
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021630503)
http://linked.open...iv/cisloPeriodika
  • 3
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 522501
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/05:PU50363
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Neural network, Non-linear Modelling, Predictive control (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • GR - Řecká republika
http://linked.open...ontrolniKodProRIV
  • [7E70A6068642]
http://linked.open...i/riv/nazevZdroje
  • WSEAS Transactions on Circuits
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 2005
http://linked.open...iv/tvurceVysledku
  • Pivoňka, Petr
  • Schmidt, Michal
  • Nepevný, Petr
  • Vychodil, Hynek
http://linked.open...n/vavai/riv/zamer
issn
  • 1109-2734
number of pages
http://localhost/t...ganizacniJednotka
  • 26220
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