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Event-based State Estimation in Cyber-Physical Systems Open Access


Other title
State Estimation
Cyber-Physical Systems
Event-Triggered Systems
Type of item
Degree grantor
University of Alberta
Author or creator
Shi, Dawei
Supervisor and department
Chen, Tongwen (Electrical and Computer Engineering)
Examining committee member and department
Marquez, Horacio (Electrical and Computer Engineering)
Zhao, Qing (Electrical and Computer Engineering)
Chen, Tongwen (Electrical and Computer Engineering)
Liu, Jinfeng (Chemical and Materials Engineering)
Zhou, Kemin (Electrical and Computer Engineering, Louisiana State University)
Tavakoli, Mahdi (Electrical and Computer Engineering)
Department of Electrical and Computer Engineering
Control Systems
Date accepted
Graduation date
Doctor of Philosophy
Degree level
This thesis focuses on event-based state estimation problems in the context of cyber-physical systems (CPSs), targeting at low-complexity event-based state estimators that are optimal in a certain sense. The motivation stems from the resource limitations in the applications of CPSs (e.g., wireless sensor networks) as well as the increased computation burden in calculating the optimal state estimates caused by the event-triggering conditions. Several event-based estimation problems are formulated and solved using different approaches, including the maximum likelihood estimation approach, the approximate Gaussian filtering approach, the set-valued Kalman filtering approach and the change of probability measure approach. For all these investigations, optimal state estimates with simple structures that can be recursively calculated are obtained, which form the major contributions of this thesis. Also, the performance improvements in the sense of average estimation errors by exploiting the information contained in the event-triggering conditions are addressed either by theoretical proofs or extensive numerical simulations. Several results on communication rate analysis are proposed, which are relevant and necessary for event-based estimation, considering the potential communication resource limitations in CPSs. Based on the developed results, the outcome of the research attempts on event-based estimation is encouraging, and a distinct and systematic approach to event-based estimation seems on the horizon. The results are not only of theoretical value, but are potentially implementable to a variety of applications in industrial processes, due to the practical considerations in both the problem formulations and the design procedures.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Dawei Shi, Tongwen Chen and Ling Shi. “An event-triggered approach to state estimation with multiple point- and set-valued measurements,” Automatica, 50(6), pp. 1641-1648, 2014.Dawei Shi, Tongwen Chen and Ling Shi. “Event-triggered maximum likelihood state estimation,” Automatica, 50(1), pp. 247-254, 2014.Dawei Shi, Tongwen Chen and Ling Shi. “Event-based state estimation of linear dynamical systems: Communication rate analysis,” in Proceedings of the 2014 American Control Conference (ACC 2014), Portland, Oregon, 2014.

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