On the Stability and Feasibility of Model Predictive Control

Supriyo K. Mondal, Swapan Paruya, Singiresu S Rao

Research output: Contribution to journalArticle

Abstract

In this paper, we demonstrate the issues of feasibility, stability and performance of constrained finite receding horizon linear quadratic regulator (RHLQR) problems using primal-dual interior point (PDIP) method developed in FORTRAN. Instead of including path constraints, we have chosen sufficiently long horizon to achieve stability with finite horizon cost leading to Lyapunov function. We observed a significant improvement of stability of model predictive control using PDIP over active set method.

Original languageEnglish
Pages (from-to)380-384
Number of pages5
JournalComputer Aided Chemical Engineering
Volume31
DOIs
StatePublished - Aug 7 2012

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Model predictive control
Lyapunov functions
Costs

Keywords

  • Feasibility
  • Performance
  • Stability

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Cite this

On the Stability and Feasibility of Model Predictive Control. / Mondal, Supriyo K.; Paruya, Swapan; Rao, Singiresu S.

In: Computer Aided Chemical Engineering, Vol. 31, 07.08.2012, p. 380-384.

Research output: Contribution to journalArticle

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