Finite‐horizon fault estimation for time‐varying systems with multiple fading measurements under torus‐event–based protocols
Finite‐horizon fault estimation for time‐varying systems with multiple fading measurements under torus‐event–based protocols
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DOI：
10.1002/rnc.4640
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发表时间：
2019-07
影响因子：
3.9
通讯作者：
Yamei Ju;G. Wei;Derui Ding;Shuai Liu
中科院分区：
文献类型：
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作者：
Yamei Ju;G. Wei;Derui Ding;Shuai Liu
本文研究了一类具有随机故障和多次衰落测量的离散时变系统的有限地平线H∞故障估计问题。缺失现象可能是由不同传感器随机产生的，由满足一定概率分布的单个随机变量来表示。此外，为了减轻通信负担，采用基于环面事件的协议，仅在发生重大事件时才调度数据传输。我们提出的问题的目的是估计故障，这样，通过基于环面事件协议控制的接收信息进行多次衰落测量，H∞指数在给定的有限视界内得到满足。利用随机分析技术和平方补全方法，得到了期望时变估计量的充分条件。期望的估计量增益是通过计算两个倒推Riccati差分方程得到的。最后通过数值仿真验证了所设计的故障估计方法的有效性。
In this paper, the issue of the finite‐horizon H∞ fault estimation is dealt with for a class of discrete time‐varying systems subject to randomly occurring faults and multiple fading measurements. The missing phenomena may occur in a random way from different sensors, which is represented by an individual stochastic variable meeting a certain probability distribution. Furthermore, in order to alleviate the communication burden, the torus‐event–based protocols are adopted to schedule the data transmissions only when some significant events occur. Our aim of the presented issue is to estimate the fault such that, with multiple fading measurements via the received information governed by torus‐event–based protocols, the H∞ index is satisfied over a given finite horizon. Sufficient conditions are obtained for the desired time‐varying estimator in terms of the technique of stochastic analysis and the methods of completing squares. The desired estimator gains are calculated by working out two backward recursive Riccati difference equations. Finally, a numerical simulation is given to verify the usefulness of our designed fault estimation approach.