Nonlinear observers for perspective time-invariant linear systems

Rixat Abdursul, Hiroshi Inaba, Bijoy K. Ghosh

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Perspective dynamical systems arise in machine vision, in which only perspective observation is available. This paper proposes and studies a Luenberger-type nonlinear observer for perspective time-invariant linear systems. Assuming a given perspective time-invariant linear system to be Lyapunov stable and to satisfy some sort of detectability condition, it is shown that the estimation error converges exponentially to zero. Finally, some simple numerical examples are presented to illustrate the result obtained.

Original languageEnglish
Pages (from-to)481-490
Number of pages10
JournalAutomatica
Volume40
Issue number3
DOIs
StatePublished - Mar 2004

Keywords

  • Detectability
  • Exponential stability
  • Luenberger-type observer
  • Machine vision
  • Nonlinear observer
  • Perspective system

Fingerprint Dive into the research topics of 'Nonlinear observers for perspective time-invariant linear systems'. Together they form a unique fingerprint.

Cite this