基于自适应事件触发的离散时滞T-S模糊模型的降阶估计
Reduced Order Estimation of Discrete Time Delay T-S Fuzzy Model Based on Adaptive Event Triggering
摘要: 本文研究了离散时滞Takagi-Sugeno模糊系统的 l2-l∞ 降阶滤波器设计问题。针对离散时滞Takagi-Sugeno模糊动态系统，设计了降阶滤波器将原模型转化为线性低阶模型。该滤波器还可以用 l2-l∞ 性能近似原始系统，使用一种新的自适应事件触发方案来减少网络的通信负载和计算资源。通过将模糊降阶滤波器的滤波问题转化为凸优化问题，给出了设计模糊降阶滤波器的条件。最后，通过两个算例验证了所提设计方案的可行性和适用性。
Abstract: In this paper, the design problem of l2-l∞ reduced order filter for discrete time delay Takagi-Sugeno fuzzy systems is studied. For discrete time delay Takagi-Sugeno fuzzy dynamic sys-tems, a l2-l∞ reduced order filter is designed to transform the original model into a linear low order model. The filter can also approximate the performance of the original system, and a new adaptive event triggering scheme can be used to reduce the communication load and computing resources of the network. By transforming the filtering problem of the fuzzy reduced order filter into a convex optimization problem, the conditions for designing the fuzzy reduced order filter are given. Finally, two examples are given to verify the feasibility and applicability of the proposed design scheme.
文章引用：张亚平, 张梦瑶. 基于自适应事件触发的离散时滞T-S模糊模型的降阶估计[J]. 运筹与模糊学, 2023, 13(2): 1005-1019. https://doi.org/10.12677/ORF.2023.132104

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