Mode-dependent filter design for Markov jump systems with sensor nonlinearities in finite frequency domain

Mouquan Shen, Dan Ye, Qing Guo Wang

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)

Abstract

This paper is concerned with the filter design for Markov jump systems with incomplete transition probabilities subject to sensor nonlinearities. Moreover, the frequency of disturbance ranges in a finite interval. To set up a solvable solution to cast the filter parameters, nonlinearities induced by unknown transition probabilities are coped with the transition probability property and the S-procedure is adopted to handle sensor nonlinearities. With these strategies, sufficient conditions for the filtering error systems to be stochastically stable with the required finite frequency performance are established firstly. Then, a finite frequency filter design method is proposed in terms of linear matrix inequalities. The proposed finite frequency filter method covers the full frequency as a special case. Its effectiveness is verified by a numerical example.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalSignal Processing
Volume134
DOIs
Publication statusPublished - 1 May 2017

Keywords

  • Finite frequency domain
  • Markov jump systems
  • Sensor nonlinearities

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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