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Description
  • Classical model based predictive regulation sets the action signal magnitude in a way that ensures, that the chosen cost function will reach its minimum, which means, that the proper cost function parameters setting is crucial for the shape of transient.These parameters are usually constants that do not change their value in the course of regulation. However, given the actual condition of the regulation, their change can improve the quality of the transient. This solution reduces the adverse effects caused by the inexact model of the plant or short predictive horizon (short sample period) with regard to the length of the transient. This can occur when we use adaptive predictive control, where the dynamics and consequently also the duration of the transient are not constant.
  • Classical model based predictive regulation sets the action signal magnitude in a way that ensures, that the chosen cost function will reach its minimum, which means, that the proper cost function parameters setting is crucial for the shape of transient.These parameters are usually constants that do not change their value in the course of regulation. However, given the actual condition of the regulation, their change can improve the quality of the transient. This solution reduces the adverse effects caused by the inexact model of the plant or short predictive horizon (short sample period) with regard to the length of the transient. This can occur when we use adaptive predictive control, where the dynamics and consequently also the duration of the transient are not constant. (en)
Title
  • On-line Fuzzy Parameters Setting of Predictive Controller
  • On-line Fuzzy Parameters Setting of Predictive Controller (en)
skos:prefLabel
  • On-line Fuzzy Parameters Setting of Predictive Controller
  • On-line Fuzzy Parameters Setting of Predictive Controller (en)
skos:notation
  • RIV/00216305:26220/00:43700029!RIV/2001/MSM/262201/N
http://linked.open.../vavai/riv/strany
  • 89
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM 260000013)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
  • Pivoňka, Petr
  • Halva, Petr
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 720543
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/00:43700029
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Predictive control, Fuzzy supervisor, Adaptive control, Model-based predictive control. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [186980F8EF0E]
http://linked.open...i/riv/mistoVydani
  • Germany
http://linked.open...i/riv/nazevZdroje
  • Proceedings of East West Fuzzy Colloquium 2000, Heft 64
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Pivoňka, Petr
  • Halva, Petr
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • IPM, University of Applied Science, Zittau
https://schema.org/isbn
  • 3-00-006723-X
http://localhost/t...ganizacniJednotka
  • 26220
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