Event-Based State Estimation / Studies in Systems, Decision and Control Bd.41 (PDF)

Dawei Shi was born in Shandong Province, China. He received his B.Eng. degree in Electrical Engineering and its Automation from the Beijing Institute of Technology in 2008. In 2010, he received the financial support from the China Scholarship Council and the Provost Scholarship from the University of Alberta, where he received the Ph.D. degree on control systems in November 2014. From December 2014, he has been appointed as an Associate Professor at the School of Automation, Beijing Institute of Technology, China. In 2009, he received the Best Student Paper Award at the IEEE International Conference on Automation and Logistics. His research interests include event-based control and estimation, robust model predictive control and tuning, and wireless sensor networks. He has authored or co-authored 18 papers, most of which have been published in the top journals and conferences in the field of control systems. He also applied for a US patent as the first inventor in March2014, supported by Honeywell Process Solutions, Vancouver. He is a reviewer for a number of international journals and conferences, including Automatica, IEEE Transactions on Automatic Control, Systems & Control Letters, IEEE Conference on Decision and Control, American Control Conference, and IFAC World Congress.




Ling Shi received his B.S. degree in Electrical and Electronic Engineering from the Hong Kong University of Science and Technology in 2002 and Ph.D. degree in Control and Dynamical Systems from California Institute of Technology in 2008. He is currently an Associate Professor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology. His research interests include modeling and control of cyber-physical systems, and sensor data scheduling and sensor fusion. He has published over 30 journals papers and 60 conference papers. He is a member of the IFAC Technical Committee on Networked Systems since Oct 2011, and served in many

“This book addresses essentially the engineers (or researchers and students interested in the area of event-trigged systems). The subject turns around event-based estimation problems in a stochastic setting. This document is self-contained and it is readable with just a basic knowledge of probability theory, Kalman filtering theory, and linear algebra. … This book is clear and well written. The results presented are proven, and each chapter contains notes and references.” (Bénédicte Puig, zbMATH 1331.62010, 2016)