Switching adaptive output feedback model predictive control for a class of input-constrained linear plants

J. S. Kim, Tae Woong Yoon, H. Shim, J. H. Seo

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

An adaptive output feedback model predictive control (MPC) for an uncertain input-constrained neutrally stable linear plant using control-relevant switching is presented. By employing an input-to-state stabilising MPC as the multi-controller, switching adaptive output feedback MPC is proposed for the system. Unlike previous methods for handling uncertainties on the basis of minmax MPC laws or techniques for linear parameter varying systems, the proposed MPC scheme employs model switching to deal with modelling uncertainties through adaptation; a best model is selected for the MPC law from time to time. The proposed scheme using finite prediction horizon guarantees global stability. Simulation results are given to show the effectiveness of the scheme.

Original languageEnglish
Pages (from-to)573-582
Number of pages10
JournalIET Control Theory and Applications
Volume2
Issue number7
DOIs
Publication statusPublished - 2008 Jul 14

Fingerprint

Model predictive control
Model Predictive Control
Output Feedback
Feedback
Linear Parameter-varying Systems
Switching Control
Uncertainty Modeling
Min-max
Global Stability
Class
Horizon
Controller
Uncertainty
Controllers
Prediction
Model
Simulation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization

Cite this

Switching adaptive output feedback model predictive control for a class of input-constrained linear plants. / Kim, J. S.; Yoon, Tae Woong; Shim, H.; Seo, J. H.

In: IET Control Theory and Applications, Vol. 2, No. 7, 14.07.2008, p. 573-582.

Research output: Contribution to journalArticle

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