Simplified adaptive estimation

I. Yaesh*, U. Shaked

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A simplified adaptive scheme is suggested for the estimation of the state vector of linear systems driven by white process noise that is added to an unknown deterministic signal. The design approach is based on embedding the Kalman filter within a simplified adaptive control loop that is driven by the innovation process. The simplified adaptive loop is idle during steady-state phases that involve white driving noise only. However, when the deterministic signal is added to the driving noise signal, the simplified adaptive control loop enhances the Kalman filter gains and helps in reducing the resulting transients. The stability of the overall estimation scheme is established under strictly passive conditions of a related system. The suggested method is applied to the target acceleration estimation problem in a Theater Missile Defense scenario.

Original languageEnglish
Title of host publicationROCOND'06 - 5th IFAC Symposium on Robust Control Design, Final Program with Abstracts
PublisherIFAC Secretariat
Pages71-76
Number of pages6
EditionPART 1
ISBN (Print)9783902661104
DOIs
StatePublished - 2006

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume5
ISSN (Print)1474-6670

Keywords

  • Adaptive estimation
  • Almost strict passivity
  • Kalman filter
  • Neural networks
  • Simplified adaptive control

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