A new constant gain Kalman filter based on TP model transformation

Fan Yang, Zhen Chen*, Xiangdong Liu, Bing Liu

*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

A constant gain Kalman filter is proposed in this paper concerned with the problem of the complexity and large calculation in nonlinear system estimation. With the introduction of linear parameter varying (LPV) model and tensor product (TP) model transformation method, the nonlinear system is represented by a linear polytopic model. The transformation directly leads to the reduction of the conservativeness for the linear polytopic model gained by the parameter bounds method and avoids solving infinite number of linear matrix inequalities (LMIs). Moreover, a constant gain filter is developed based on the EKF and robust H2 filtering, which greatly reduces the calculation number. Finally, an example is employed to illustrate the effectiveness of the proposed filter.

Original languageEnglish
Title of host publicationProceedings of 2013 Chinese Intelligent Automation Conference
Subtitle of host publicationIntelligent Automation
Pages305-312
Number of pages8
DOIs
Publication statusPublished - 2013
Event2013 Chinese Intelligent Automation Conference, CIAC 2013 - Yangzhou, Jiangsu, China
Duration: 23 Aug 201325 Aug 2013

Publication series

NameLecture Notes in Electrical Engineering
Volume254 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference2013 Chinese Intelligent Automation Conference, CIAC 2013
Country/TerritoryChina
CityYangzhou, Jiangsu
Period23/08/1325/08/13

Keywords

  • LPV
  • Nonlinear system
  • Polytope
  • Robust H2 filter
  • TP

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