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State estimation for T-S fuzzy affine systems with variable quantization density

  • School of Astronautics, Harbin Institute of Technology
  • Instituto Politécnico Nacional

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

Abstract

This paper is concerned with the problem of state estimation for a class of discrete-time Takagi-Sugeno fuzzy affine systems against measurement quantization. The quantization density can be manually adjusted to satisfy different performance requirements at different time instants, which can reduce the amount of transmitted information when the performance requirement for the fuzzy filtering error system is not critical. With the aid of a fuzzy-basis-dependent Lyapunov function and the S-procedure approach, sufficient conditions on the existence of the desired H∞ filters are established to ensure that the fuzzy filtering error system is asymptotically stable with a prescribed H∞ performance index. Finally, a practical example of single-link robot arm is provided to illustrate the effectiveness as well as the smaller transmitted information burden of the proposed state estimation strategy.

Original languageEnglish
Title of host publicationProceedings of 6th International Conference on Intelligent Control and Information Processing, ICICIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages274-279
Number of pages6
ISBN (Electronic)9781479917174
DOIs
StatePublished - 20 Jan 2016
Externally publishedYes
Event6th International Conference on Intelligent Control and Information Processing, ICICIP 2015 - Wuhan, Hubei, China
Duration: 26 Nov 201528 Nov 2015

Publication series

NameProceedings of 6th International Conference on Intelligent Control and Information Processing, ICICIP 2015

Conference

Conference6th International Conference on Intelligent Control and Information Processing, ICICIP 2015
Country/TerritoryChina
CityWuhan, Hubei
Period26/11/1528/11/15

Keywords

  • TCS fuzzy affine systems
  • filter design
  • signal transmission delays
  • variable quantization density

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