Stabilization of Takagi–Sugeno fuzzy Hidden Markov Jump Systems with memory sampled-data control

R. Rakkiyappan, V. Sharmila, K. Janani, Ardak Kashkynbayev

Research output: Contribution to journalArticlepeer-review

Abstract

The stability of Takagi–Sugeno fuzzy hidden Markovian jump systems by employing a memory sampled-data control (SDC) scheme that includes a constant signal transmission delay is investigated. The asynchronous situation between the system plant and the controller is represented using the hidden Markov model. The stability of the provided model is ensured by implication of the fuzzy time-scheduled Lyapunov functional (LF), and the sufficient conditions are derived in the form of linear matrix inequalities (LMIs). This simplifies the utilization and generalization of the analysis results, as they exhibit convexity in the subsystem matrix. Additionally, it diminishes the influence of external disturbances by employing the H norm bound. To acquire the required time-dependent memory SDC, it is necessary to solve this set of LMIs. The efficacy and feasibility of the proposed method is established by attaining stability for a chaotic Lorenz system using the T–S fuzzy Hidden Markov Jump Systems with Memory SDC.

Original languageEnglish
Pages (from-to)204-217
Number of pages14
JournalMathematics and Computers in Simulation
Volume226
DOIs
Publication statusPublished - Dec 2024

Keywords

  • Hidden Markov jump system
  • Memory sampled-data control
  • Time-scheduled Lyapunov functional
  • T–S fuzzy system

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science
  • Numerical Analysis
  • Modelling and Simulation
  • Applied Mathematics

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