Adaptive unified predictive control applied to first-order-plus-dead-time processes to eliminate unknown class of deterministic disturbance

Shu Kai Lin*, An-Chen Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel Adaptive Unified Predictive Control method (Adaptive-UPC) is proposed and applied to the first-order-plus-dead-time (FOPDT) process models with model uncertainties under unknown deterministic disturbances. Based on Indirect Self-tuning Regulator, this new control structure is constructed by combining UPC controller, Recursive Least-Squares Estimation with forgetting factor (RLS with forgetting factor) and Variable Regression Estimation (VRE). The simulation results show that the method can be effectively applied to first-order-plus-dead-time (FOPDT) process models with uncertain process parameters (gain, time constant and dead-time) and unknown deterministic disturbance.

Original languageEnglish
Title of host publicationIEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation
Pages149-156
Number of pages8
DOIs
StatePublished - 11 Aug 2011
EventSymposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011 - Paris, France
Duration: 11 Apr 201115 Apr 2011

Publication series

NameIEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation

Conference

ConferenceSymposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011
CountryFrance
CityParis
Period11/04/1115/04/11

Keywords

  • First order plus dead time process
  • Model uncertainty
  • RLS with forgetting factor
  • Unified predictive control
  • Unknown disturbance
  • VRE

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