Parameter-dependent H2 state estimation for nonlinearl systems

Yin Yu, Zhen Li, Xiangdong Liu, Bing Liu

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

2 Citations (Scopus)

Abstract

The state estimation of general nonlinear systems is investigated through a parameter-dependent approach. This paper adopts the polytopic approximation for the nonlinear systems, which facilitates the application of analytical approaches for resultant convex-bounded linear systems into the given nonlinear systems. The design of a high performance H2 state estimator is firstly determined by solving a convex optimization problem constrained by relaxed linear matrix inequalities (LMIs). The tensor product (TP) model transformation is then adopted to obtain the polytopic linearization. Specifically, A new process is presented to correct the result of the TP model transformation such that a necessary condition to solve the state estimation problem is assured. Finally, a numerical simulation is performed to illustrate the design process and verify the performance.

Original languageEnglish
Title of host publicationProceedings of the 34th Chinese Control Conference, CCC 2015
EditorsQianchuan Zhao, Shirong Liu
PublisherIEEE Computer Society
Pages979-984
Number of pages6
ISBN (Electronic)9789881563897
DOIs
Publication statusPublished - 11 Sept 2015
Event34th Chinese Control Conference, CCC 2015 - Hangzhou, China
Duration: 28 Jul 201530 Jul 2015

Publication series

NameChinese Control Conference, CCC
Volume2015-September
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference34th Chinese Control Conference, CCC 2015
Country/TerritoryChina
CityHangzhou
Period28/07/1530/07/15

Keywords

  • Nonlinear state estimation
  • linear matrix inequalities (LMIs)
  • parameter-dependent H filter
  • tensor product (TP) model transformation

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