Event-triggered remote state estimation over a collision channel with incomplete information

Abstract

This paper investigates the stochastic event-triggered remote state estimation problem over a collision channel. The remote estimator does not have the knowledge of the measurement in the case of collision and the origin of the data packet in the case of successful transmission, resulting in the non-Gaussianity of the estimation process in the two cases. By using a commonly used Gaussian approximation method, the posterior distribution of the system state is proved to be a mixture of two Gaussians and a mixture of three Gaussians in the cases of collision and successful transmission, respectively. Then an approximate minimum mean squared error estimator with adaptive weights is proposed, and the weights convexly combine the estimates for the possible transmission situations. Moreover, the proposed estimator is also shown to be conventional forms under three extreme situations. Finally, numerical results illustrate the effectiveness of the proposed estimator based on the incomplete information.

Keywords:

• Event-triggered estimation
• minimum mean squared error
• collision channel
• incomplete information

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data sharing is not applicable to this article as no new data were created or analysed in this study.

Additional information

Funding

This work was financially supported by the National Natural Science Foundation of China [grant number 62273320]. The material in this paper was not presented at any conference.

Notes on contributors

Di Deng

Di Deng received her B.E. degree in mathematics and applied mathematics, Anhui University, Hefei, China, in 2017. She is currently working toward the Ph.D. degree with the Department of Automation, University of Science and Technology of China, Hefei, China. Her current research interests include cyber-physical systems, state estimation and wireless sensor networks.

Junlin Xiong

Junlin Xiong received his B.E. and M.S. degrees from Northeastern University, China, in 2000 and 2003, respectively, and his PhD degree from the University of Hong Kong, Hong Kong Special Administrative Region of China, in 2007. From 2007 to 2010, he was a research associate at the University of New South Wales at the Australian Defence Force Academy, Australia. In March 2010, he joined the University of Science and Technology of China, where he is currently a professor in the Department of Automation. Currently, he is an Associate Editor for the IET Control Theory and Application. His current research interests are in the fields of negative imaginary systems, large-scale systems and networked control systems.