期刊
AUTOMATICA
卷 94, 期 -, 页码 458-464出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2018.03.031
关键词
Recursive filter; Quantization effect; Resilient property; Sensor failure; Event-triggered communication
资金
- Research Fund for the Taishan Scholar Project of Shandong Province of China
- National Natural Science Foundation of China [61490701, 61525305, 61473163, 61522309, 61733009]
- Royal Society of the UK
- Alexander von Humboldt Foundation of Germany
- Special Fund of Suzhou-Tsinghua Innovation Leading Action [2016SZ0202]
This paper is concerned with the remote state estimation problem for a class of discrete-time stochastic systems. An event-triggered scheme is exploited to regulate the sensor-to-estimator communication in order to preserve limited network resources. A situation is considered where the sensors are susceptible to possible failures and the signals are quantized before entering the network. Furthermore, the resilience issue for the filter design is taken into account in order to accommodate the possible gain variations in the course of filter implementation. In the simultaneous presence of measurement quantizations, sensor failures and gain variations, an event-triggered filter is designed to minimize certain upper bound of the covariance of the estimation error in terms of the solution to Riccati-like difference equations. Further analysis demonstrates the monotonicity of the minimized upper bound with respect to the value of thresholds. Subsequently, a sufficient condition is also established for the convergence of the steady-state filter. A numerical example is presented to verify the effectiveness of the proposed filtering algorithm. (C) 2018 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据