Nonlinear state estimation with nonlinear equality constraints

Jinya Su, Wen Hua Chen, Baibing Li

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)

Abstract

This paper investigates the problem of state estimation of nonlinear systems with nonlinear equality constraints. By treating the nonlinear equality constraints as part of the new coordinate, a diffeomorphism is found such that an unconstrained reduced-order system is obtained. The existing unconstrained estimators can be applied to obtain the reduced-order state estimate. Then, based on the inverse transformation, the original states can be obtained by combing the reduced-order state estimate and the nonlinear equality constraints. Compared with the traditional model reduction approach, there exists one more freedom to choose the independent variables in the proposed approach. Compared with the null space approach, the proposed approach can handle nonlinear estimation with general nonlinear equality constraints. Finally, the estimation problem for a moving vehicle on a given circular path is used to illustrate the principle of the proposed approach.

Original languageEnglish
Title of host publication53rd IEEE Conference on Decision and Control,CDC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages322-327
Number of pages6
EditionFebruary
ISBN (Electronic)9781467360906
ISBN (Print)9781479977468
DOIs
Publication statusPublished - Dec 2014
Event2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States
Duration: 15 Dec 201417 Dec 2014

Publication series

NameProceedings of the IEEE Conference on Decision and Control
NumberFebruary
Volume2015-February
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Country/TerritoryUnited States
CityLos Angeles
Period15/12/1417/12/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Reduced order systems
  • Null space
  • Vehicles
  • Roads
  • Noise measurement
  • State estimation

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