State observer for a class of nonlinear systems and its application to machine vision

Xinkai Chen, Hiroyuki Kano

Research output: Contribution to journalArticlepeer-review

77 Citations (Scopus)


In this note, we consider the state observer problem for a class of nonlinear systems which are usually encountered in the machine vision study. The formulation of the state observer is motivated by the sliding mode methods and adaptive control techniques. The proposed observer is applied to the identification problems of the motion parameters and space position of a moving object by using the perspective observation of a single point. It is clarified that the rotation parameters can be observed by using the observation of one camera, and the position and translation parameters cannot be observed by using one camera and must appeal to stereo vision. Simulation results show that the proposed algorithm is effective.

Original languageEnglish
Pages (from-to)2085-2091
Number of pages7
JournalIEEE Transactions on Automatic Control
Issue number11
Publication statusPublished - 2004 Nov 1


  • Machine vision
  • Nonlinear system
  • Perspective observation
  • State observer

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'State observer for a class of nonlinear systems and its application to machine vision'. Together they form a unique fingerprint.

Cite this