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  • The paper deals with the problem of modelling and control using the Local Model Network (LMN). The idea is based on development of multiple local models for the whole operating range of the controlled process. The local models are then smoothly connected using the validity or weighting functions to provide a nonlinear global model of the plant. For saving the computational load, linear model is obtained by interpolating the parameters of local models at each sample instant and then used in Model Predictive Control (MPC) framework to calculate the future behaviour of the process. The supervisory program, based on a nonlinear global model, computes desired values of manipulated variables leading to minimum utility consumption. The approach is verified in a control of model of a heat exchanger.
  • The paper deals with the problem of modelling and control using the Local Model Network (LMN). The idea is based on development of multiple local models for the whole operating range of the controlled process. The local models are then smoothly connected using the validity or weighting functions to provide a nonlinear global model of the plant. For saving the computational load, linear model is obtained by interpolating the parameters of local models at each sample instant and then used in Model Predictive Control (MPC) framework to calculate the future behaviour of the process. The supervisory program, based on a nonlinear global model, computes desired values of manipulated variables leading to minimum utility consumption. The approach is verified in a control of model of a heat exchanger. (en)
Title
  • Local Model Networks for Modelling and Predictive Control of Nonlinear Systems
  • Local Model Networks for Modelling and Predictive Control of Nonlinear Systems (en)
skos:prefLabel
  • Local Model Networks for Modelling and Predictive Control of Nonlinear Systems
  • Local Model Networks for Modelling and Predictive Control of Nonlinear Systems (en)
skos:notation
  • RIV/70883521:28140/09:63508771!RIV10-GA0-28140___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GP102/09/P243)
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
  • 323983
http://linked.open...ai/riv/idVysledku
  • RIV/70883521:28140/09:63508771
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Predictive control; Local Model Networks; Heat-exchanger; Optimization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [521B4A4E0A9C]
http://linked.open...v/mistoKonaniAkce
  • Madrid, Spain
http://linked.open...i/riv/mistoVydani
  • Madrid
http://linked.open...i/riv/nazevZdroje
  • 23rd European Conference on Modelling and Simulation
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Bobál, Vladimír
  • Chalupa, Petr
  • Novák, Jakub
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • ECMS Sp.
https://schema.org/isbn
  • 978-0-9553018-8-9
http://localhost/t...ganizacniJednotka
  • 28140
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