Journal
AUTOMATICA
Volume 94, Issue -, Pages 458-464Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2018.03.031
Keywords
Recursive filter; Quantization effect; Resilient property; Sensor failure; Event-triggered communication
Funding
- 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]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available