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Mean square admissibility analysis and controller design of stochastic T–S fuzzy singular systems based on the fuzzy lyapunov function method

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  • Zhong, Jiao
  • Qiao, Liang

Abstract

This paper explores the stochastic T–S fuzzy singular system problem from both the stability and controller design viewpoints. A Lyapunov-inspired fuzzy formulation is proposed to derive matrix-based criteria ensuring mean-square stability, represented through Linear Matrix Inequalities(LMIs). By introducing auxiliary variables and inequality-scaling operations, the method effectively handles the membership functions involved in the analysis, thereby reducing conservatism compared with conventional Lyapunov approaches. Additionally, both parallel distributed compensation(PDC) and non-PDC control strategies are developed to maintain system stability and adaptability across different operating scenarios. The feasibility and efficiency of the proposed framework are verified through simulation experiments and a practical application example.

Suggested Citation

  • Zhong, Jiao & Qiao, Liang, 2026. "Mean square admissibility analysis and controller design of stochastic T–S fuzzy singular systems based on the fuzzy lyapunov function method," Applied Mathematics and Computation, Elsevier, vol. 525(C).
    • Handle: RePEc:eee:apmaco:v:525:y:2026:i:c:s0096300326001268
    DOI: 10.1016/j.amc.2026.130074
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