Eigenvector approach for order reduction of singularly perturbed linear-quadratic optimal control problems

V. Kecman, S. Bingulac, Z. Gajic

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

In this paper we show how to decompose the singularly perturbed algebraic Riccati equation and the corresponding linear-quadratic optimal control problem at steady state in terms of reduced-order pure-slow and pure-fast problems by using the eigenvector approach. The eigenvector approach should be used for decomposition of singularly perturbed control systems in the cases when the singular perturbation parameter is not very small. In such cases the decomposition methods based on series expansions, fixed point iterations, subspace iterations, and Newton iterations, either fail to produce solutions of the corresponding algebraic equations or display very slow convergence.

Original languageEnglish (US)
Pages (from-to)151-158
Number of pages8
JournalAutomatica
Volume35
Issue number1
DOIs
StatePublished - Jan 1 1999

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Algebraic Riccati equations
  • Eigenvectors
  • Linear optimal regulators
  • Optimal control
  • Order reduction
  • Singular perturbations

Fingerprint Dive into the research topics of 'Eigenvector approach for order reduction of singularly perturbed linear-quadratic optimal control problems'. Together they form a unique fingerprint.

Cite this