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PI-type event-triggered H∞ filter for networked T-S fuzzy systems using affine matched membership function approach
Applied Mathematics and Computation ( IF 3.5 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.amc.2020.125420
W. Kwon , Yongsik Jin , S.M. Lee

Abstract This paper handles a design of event-triggered H∞ filter for T-S fuzzy systems in the connection of network communication. The sampled-data fuzzy filter, which take into account both the measurement output and the fuzzy consequent parameter as the sampled signal, is expressed as a fuzzy system with a time-varying delay including the event-triggering variable. Under these considerations, a novel proportional-plus-integral (PI) event triggering condition is proposed to alleviate network allocation. Based time-delay approach, the stability of the filtering error systems is guaranteed by a new Lyapunov Kravoskii functional and by employing generalized free-weighting matrix integral inequality. Furthermore, an affine matched membership based distributed-filter (AMDF) is designed to improve the H∞ performance, utilizing affine transformed membership function as a membership function of fuzzy filter. The affine matched membership function relaxes the parameterized stability condition due to the deviation bounds of sampled fuzzy membership function between consecutive sampling times. To show the effectiveness of proposed method, the results are compared with the unused ones.

中文翻译:

使用仿射匹配隶属函数方法的网络 TS 模糊系统的 PI 型事件触发 H∞ 滤波器

摘要 本文针对网络通信中的TS模糊系统,设计了事件触发的H∞滤波器。采样数据模糊滤波器将测量输出和模糊结果参数都考虑为采样信号,它被表示为具有时变延迟的模糊系统,包括事件触发变量。在这些考虑下,提出了一种新的比例加积分 (PI) 事件触发条件来减轻网络分配。基于时延方法,滤波误差系统的稳定性由新的 Lyapunov Kravoskii 泛函和采用广义自由加权矩阵积分不等式保证。此外,基于仿射匹配隶属度的分布式滤波器 (AMDF) 旨在提高 H∞ 性能,利用仿射变换隶属函数作为模糊滤波器的隶属函数。由于连续采样时间之间采样模糊隶属函数的偏差界限,仿射匹配隶属函数放宽了参数化稳定性条件。为了显示所提出方法的有效性,将结果与未使用的结果进行比较。
更新日期:2020-11-01
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