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Kalman filtering for descriptor systems with current and delayed measurements

  • Haoqian Wang*
  • , Huanshui Zhang
  • , Guangren Duan
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen
  • Harbin Institute of Technology

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

Abstract

A class of discrete-time Kalman filtering problem for the descriptor time-varying systems with current and delayed measurements is considered. Using the known maximum likelihood (ML) estimation results and the method of measurements reorganization, the optimal Kalman filter and corresponding Riccati equations for descriptor systems involving current and delayed measurements are derived. Our solution does not require system augmentation or system transformation, and the estimator is given in terms of two Riccati equations of the same order as that of the system state. A simple algorithm is presented for the problem.

Original languageEnglish
Title of host publication2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Pages2014-2018
Number of pages5
StatePublished - 2004
Event8th International Conference on Control, Automation, Robotics and Vision (ICARCV) - Kunming, China
Duration: 6 Dec 20049 Dec 2004

Publication series

Name2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Volume3

Conference

Conference8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Country/TerritoryChina
CityKunming
Period6/12/049/12/04

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