Gain Scheduled Fault Detection Filter for Markovian Jump Linear System with Nonhomogeneous Markov Chain

Leonardo Carvalho*, Jonathan M. Palma, Cecília F. Morais, Bayu Jayawardhana, Oswaldo L.V. Costa

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
53 Downloads (Pure)

Abstract

In a networked control system scenario, the packet dropout is usually modeled by a time-invariant (homogeneous) Markov chain (MC) process. However, from a practical point of view, the probabilities of packet loss can vary in time and/or probability parameter dependency. Therefore, to design a fault detection filter (FDF) implemented in a semi-reliable communication network, it is important to consider the variation in time of the network parameters, by assuming the more accurate scenario provided by a nonhomogeneous jump system. Such a premise can be properly taken into account within the linear parameter varying (LPV) framework. In this sense, this paper proposes a new design method of (Formula presented.) gain-scheduled FDF for Markov jump linear systems under the assumption of a nonhomogeneous MC. To illustrate the applicability of the theoretical solution, a numerical simulation is presented.

Original languageEnglish
Article number1713
Number of pages21
JournalMathematics
Volume11
Issue number7
DOIs
Publication statusPublished - 3-Apr-2023

Keywords

  • fault-detection filter
  • H norm
  • LMI relaxations
  • Markovian jump linear system
  • nonhomogeneous Markov chains

Fingerprint

Dive into the research topics of 'Gain Scheduled Fault Detection Filter for Markovian Jump Linear System with Nonhomogeneous Markov Chain'. Together they form a unique fingerprint.

Cite this