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  • The application of fuzzy clustering and local models for modelling and control of an evaporator is studied in the paper. The main idea is based on development of the local linear models for the whole operating range of the controlled process. The number of local models is iteratively increased until the modelling performance is reached. The position of the local model is obtained via clustering and parameters of the local models are identified using local least squares method. The nonlinear plant is then approximated by a set of locally valid sub-models, which are smoothly connected using the validity function. The parameters for the GPC controller are computed at each sampling interval from the linearization of LMN. The proposed identification and control method is illustrated by the simulation study on the evaporator.
  • The application of fuzzy clustering and local models for modelling and control of an evaporator is studied in the paper. The main idea is based on development of the local linear models for the whole operating range of the controlled process. The number of local models is iteratively increased until the modelling performance is reached. The position of the local model is obtained via clustering and parameters of the local models are identified using local least squares method. The nonlinear plant is then approximated by a set of locally valid sub-models, which are smoothly connected using the validity function. The parameters for the GPC controller are computed at each sampling interval from the linearization of LMN. The proposed identification and control method is illustrated by the simulation study on the evaporator. (en)
Title
  • Modelling and Predictive Control of an Evaporator using Local Model Network
  • Modelling and Predictive Control of an Evaporator using Local Model Network (en)
skos:prefLabel
  • Modelling and Predictive Control of an Evaporator using Local Model Network
  • Modelling and Predictive Control of an Evaporator using Local Model Network (en)
skos:notation
  • RIV/70883521:28140/10:63508847!RIV11-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
  • 271921
http://linked.open...ai/riv/idVysledku
  • RIV/70883521:28140/10:63508847
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • fuzzy modelling; nonlinear models; neural networks; least-squares identification; predictive control (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [691BAB262E89]
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://localhost/t...ganizacniJednotka
  • 28140
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