Stability analysis and fuzzy control for markovian jump nonlinear systems with partially unknown transition probabilities

Min Kook Song, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper is concerned with exploring an extended approach for the stability analysis and synthesis for Markovian jump nonlinear systems (MJNLSs) via fuzzy control. The Takagi-Sugeno (T-S) fuzzy model is employed to represent the MJNLSs with incomplete transition description. In this paper, not all the elements of the rate transition matrices (RTMs), or probability transition matrices (PTMs) are assumed to be known. By fully considering the properties of the RTMs and PTMs, sufficient criteria of stability and stabilization is obtained in both continuous and discrete-time. Stabilization conditions with a mode-dependent fuzzy controller are derived for Markovian jump fuzzy systems in terms of linear matrix inequalities (LMIs), which can be readily solved by using existing LMI optimization techniques. Finally, illustrative numerical examples are provided to demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)587-596
Number of pages10
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE97-A
Issue number2
DOIs
Publication statusPublished - 2014 Jan 1

Fingerprint

Jump System
Transition Matrix
Fuzzy control
Fuzzy Control
Transition Probability
Nonlinear systems
Stability Analysis
Nonlinear Systems
Unknown
Linear matrix inequalities
Matrix Inequality
Linear Inequalities
Stabilization
Takagi-Sugeno Fuzzy Model
Fuzzy systems
Fuzzy Controller
Fuzzy Systems
Optimization Techniques
Discrete-time
Synthesis

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

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