Dynamical Analysis of T–S Fuzzy Financial Systems: A Sampled-Data Control Approach

Bhagyaraj Thangavel, Sabarathinam Srinivasan, Thamilmaran Kathamuthu, Guisheng Zhai, Nallappan Gunasekaran

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper investigates the sampled-data stabilization of the Takagi–Sugano (T–S) fuzzy system, focusing on the existence of extreme event (EE) and its application to the financial model. The mathematical model of finance system is constructed through real time hardware experiment for the first time. The EE is identified in certain ranges of system parameters, is characterized and confirmed through numerical, analytical and experimental investigations. The stability analysis confirms that the EE occurs via an interior crisis phenomenon. The dynamical system is identified through bifurcation analysis and its corresponding Lyapunov exponent. The second phase of the manuscript is that, by building an appropriate Lyapunov function, sufficient conditions are derived to guarantee that the addressed T–S fuzzy financial system is asymptotically stable. The proposed stability conditions are expressed in terms of linear matrix inequalities (LMIs). In addition, the sampled-data control techniques are used to stabilize the EE. Finally, the simulation result is presented to support the proposed control scheme.

Original languageEnglish
JournalInternational Journal of Fuzzy Systems
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Extreme event
  • Hamilton–Jacobi inequality
  • Linear matrix inequality
  • Lyapunov spectra
  • Sampled-data control
  • T–S fuzzy method

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Computational Theory and Mathematics
  • Artificial Intelligence

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