Transmitted-Data-Driven Convergent Iterative Observer-Based Fault Estimation for T-S Fuzzy Systems With Local Nonlinearities and Faults

被引:1
作者
Huang, Sheng-Juan [1 ]
Liu, Xiao-Meng [1 ]
Guo, Liang-Dong [1 ]
Zhang, Da-Qing [1 ]
Wu, Li-Bing [1 ]
机构
[1] Univ Sci & Technol Liaoning, Sch Sci, Anshan 114051, Liaoning, Peoples R China
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2025年 / 55卷 / 02期
基金
中国国家自然科学基金;
关键词
Observers; Estimation; Iron; Iterative methods; Convergence; Nonlinear systems; Actuators; Vectors; Real-time systems; Fuzzy sets; Convergent iterative observers (CIOs); effective observers (EOs); offline fault estimation (FE); Takagi-Sugeno (T-S) fuzzy systems; transmitted data driven; TOLERANT CONTROLLER-DESIGN;
D O I
10.1109/TSMC.2024.3496713
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, based on the discrete sampled output data received through the wireless transmission from the system (equipment) represented by Takagi-Sugeno (T-S) fuzzy models with local nonlinearities and faults, a data-driven-based initial and iterative observers are designed to realize the offline fault estimation (FE). The observers do not rely entirely on continuous measured output and do not need to interface docking with the original system equipment. In the FE process of the work, an iterative estimation convergence theorem (IECT) is proposed, which is a new breakthrough for the convergence theory of estimation mean sequence in the literature. The IECT can guarantee the obtained offline iterative FE sequence from the transmitted-data-driven observers to be convergent in certain conditions. Two numerical examples are introduced to test the proposed method.
引用
收藏
页码:1116 / 1125
页数:10
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