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Description
  • In this contribution we present application of model-based predictive controller based on mixture distribution, i.e. a set of parallel models, to CSTR process. This process is highly non-linear. Presented MPC is based on a mixture of linearized models in several operating points parameterized by their probabilities estimated on-line. Provided that the operating point of the process lies within the given set defined by convex envelope of the operating points presented MPC ensures %22soft switching%22 between the individual models. The on-line estimation of model probabilities is done by a set of Kalman filters in the normalized form. The good performance of algorithm for model probability estimation is very important part of presented MPC algorithm because the resulting MPC is parameterized by them.
  • In this contribution we present application of model-based predictive controller based on mixture distribution, i.e. a set of parallel models, to CSTR process. This process is highly non-linear. Presented MPC is based on a mixture of linearized models in several operating points parameterized by their probabilities estimated on-line. Provided that the operating point of the process lies within the given set defined by convex envelope of the operating points presented MPC ensures %22soft switching%22 between the individual models. The on-line estimation of model probabilities is done by a set of Kalman filters in the normalized form. The good performance of algorithm for model probability estimation is very important part of presented MPC algorithm because the resulting MPC is parameterized by them. (en)
Title
  • Design and Analysis of Model based Predictive Controllers
  • Design and Analysis of Model based Predictive Controllers (en)
skos:prefLabel
  • Design and Analysis of Model based Predictive Controllers
  • Design and Analysis of Model based Predictive Controllers (en)
skos:notation
  • RIV/68407700:21230/05:00107697!RIV10-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • V
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
  • 517354
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/05:00107697
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Adaptive control; Mixture distribution; Model predictive control; Model probability estimation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [CE556305496E]
http://linked.open...v/mistoKonaniAkce
  • Praha
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • Proceedings of Workshop 2005
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Havlena, Vladimír
  • Pekař, Jaroslav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • České vysoké učení technické v Praze
https://schema.org/isbn
  • 80-01-03201-9
http://localhost/t...ganizacniJednotka
  • 21230
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