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<p>In this paper, the problem of observer-based fault-detection and fault-tolerant control for two-dimensional (2-D) polynomial fuzzy large-scale systems is investigated. Firstly, a 2-D polynomial fuzzy model is proposed for a kind of 2-D discrete nonlinear large-scale system, with the second Fornasini-Marchesini (FM) model as the local polynomial model. The system is monitored in real time to obtain fault information, after which a fault detection observer is constructed and a fault estimation algorithm is proposed. Subsequently, the fault information is employed for designing an effective <i>H</i><sub>∞</sub> controller to guarantee that the system maintains stable functioning and expected performance in the event of the fault. The analysis of the polynomial fuzzy large-scale system is based on polynomial Lyapunov functions. In addition, the derived stability and stabilization conditions are represented by sum of squares (SOS) and can be numerically solved by SOSTOOLS. Finally, the effectiveness of the proposed method is verified through simulation examples.</p>

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Observer-based H∞ Fault-tolerant Control for 2-D Polynomial Fuzzy Large-scale Systems With Fault-detection

  • 期刊论文

  • 发表日期：

    2025年5月14日

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  • Yutong Li,
  • Lizhen Li

摘要

In this paper, the problem of observer-based fault-detection and fault-tolerant control for two-dimensional (2-D) polynomial fuzzy large-scale systems is investigated. Firstly, a 2-D polynomial fuzzy model is proposed for a kind of 2-D discrete nonlinear large-scale system, with the second Fornasini-Marchesini (FM) model as the local polynomial model. The system is monitored in real time to obtain fault information, after which a fault detection observer is constructed and a fault estimation algorithm is proposed. Subsequently, the fault information is employed for designing an effective H∞ controller to guarantee that the system maintains stable functioning and expected performance in the event of the fault. The analysis of the polynomial fuzzy large-scale system is based on polynomial Lyapunov functions. In addition, the derived stability and stabilization conditions are represented by sum of squares (SOS) and can be numerically solved by SOSTOOLS. Finally, the effectiveness of the proposed method is verified through simulation examples.