Xiaohua Ge, Qing-Long Han, Xian-Ming Zhang, Derui Ding. Dynamic Event-triggered Control and Estimation: A Survey. International Journal of Automation and Computing. https://doi.org/10.1007/s11633-021-1306-z
Citation: Xiaohua Ge, Qing-Long Han, Xian-Ming Zhang, Derui Ding. Dynamic Event-triggered Control and Estimation: A Survey. International Journal of Automation and Computing. https://doi.org/10.1007/s11633-021-1306-z

Dynamic Event-triggered Control and Estimation: A Survey

doi: 10.1007/s11633-021-1306-z
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  • Author Bio:

    Xiaohua Ge received the B. Eng. degree in electronics and information engineering from Nanchang Hangkong University, China in 2008, the M. Eng. degree in control theory and control engineering from Hangzhou Dianzi University, China in 2011, and the Ph. D. degree in computer engineering from Central Queensland University, Australia in 2014. From 2011 to 2013, he was a research assistant with Centre for Intelligent and Networked Systems, Central Queensland University, where he was a research fellow in 2014. From 2015 to 2017, he was a research fellow with Griffith School of Engineering, Griffith University, Australia. He is currently a senior lecturer with School of Software and Electrical Engineering, Swinburne University of Technology, Australia. He is a Highly Cited Researcher according to Clarivate Analytics. He is a Senior Member of IEEE. He received the 2019 IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award, the 2020 IEEE/CAA Journal of Automatica Sinica Outstanding Reviewer Award, the 2017 IEEE Transactions on Cybernetics Outstanding Reviewer Award, and the 2017 International Journal of Automation and Computing Outstanding Reviewer Award. He is an Associate Editor of the IEEE Transaction on Systems, Man, and Cybernetics: Systems. His research interests include networked, event-triggered, secure, and intelligent control and estimation, and their applications in autonomous vehicles and connected vehicles. E-mail: xge@swin.edu.au ORCID iD: 0000-0003-0180-0897

    Qing-Long Han received the B. Sc. degree in mathematics from Shandong Normal University, China in 1983, and the M.Sc. and Ph. D. degrees in control engineering from East China University of Science and Technology, China in 1992 and 1997, respectively. He is Pro Vice-Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology, Australia. He held various academic and management positions at Griffith University and Central Queensland University, Australia. He was a Highly Cited Researcher in both Engineering and Computer Science (Clarivate Analytics, 2019−2020). He was one of Australia′s Top 5 Lifetime Achievers (Research Superstars) in Engineering and Computer Science (The Australian′s 2020 Research Magazine). He was the recipient of the 2021 M. A. Sargent Medal (the Highest Award of the Electrical College Board of Engineers Australia), the 2020 IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award, the 2020 IEEE Transactions on Industrial Informatics Outstanding Paper Award, and the 2019 IEEE SMC Society Andrew P. Sage Best Transactions Paper Award. He is a Fellow of the Institute of Electrical and Electronic Engineers and the Institution of Engineers Australia. He has served as an AdCom Member of IEEE Industrial Electronics Society (IES), a Member of IEEE IES Fellow Committee, and Chair of IEEE IES Technical Committee on Networked Control Systems. He is Co-Editor of Australian Journal of Electrical and Electronic Engineering, an Associate Editor for 12 international journals, including IEEE Transactions on Cybernetics, IEEE Transactions on Industrial Informatics, IEEE Industrial Electronics Magazine, IEEE/CAA Journal of Automatica Sinica, Control Engineering Practice, Information Sciences, and International Journal of Automation and Computing, and a Guest Editor for 13 special issues. His research interests include networked control systems, multi-agent systems, time-delay systems, smart grids, unmanned surface vehicles, and neural networks. E-mail: qhan@swin.edu.au (Corresponding author) ORCID iD: 0000-0002-7207-0716

    Xian-Ming Zhang received the M. Sc. degree in applied mathematics and the Ph. D. degree in control theory and control engineering from Central South University, China in 1992 and 2006, respectively. In 1992, he joined Central South University, where he was an associate professor with School of Mathematics and Statistics. From 2007 to 2014, he was a post-doctoral research fellow and a lecturer with School of Engineering and Technology, Central Queensland University, Australia. From 2014 to 2016, he was a lecturer with the Griffith School of Engineering, Griffith University, Australia. In 2016, he joined the Swinburne University of Technology, Australia, where he is currently an associate professor with School of Software and Electrical Engineering. He is a Highly Cited Researcher according to Clarivate Analytics. He is a Senior Member of IEEE. He was a recipient of second National Natural Science Award in China in 2013, and first Hunan Provincial Natural Science Award in Hunan Province in China in 2011, both jointly with Prof. M. Wu and Prof. Y. He. He was also a recipient of the 2020 IEEE Transactions on Industrial Informatics Outstanding Paper Award, the 2019 IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award, and the 2016 IET Control Theory and Applications Premium Award. He is an Associate Editor of the IEEE Transactions on Cybernetics, Journal of the Franklin Institute, International Journal of Control, Automation, and Systems, Neurocomputing, and Neural Processing Letters. His research interests include \begin{document}$H_{\infty} $\end{document} filtering, event-triggered control systems, networked control systems, neural networks, distributed systems, and time-delay systems. E-mail: xianmingzhang@swin.edu.au ORCID iD: 0000-0003-0691-5386

    Derui Ding received the B. Sc. degree in industry engineering and the M. Sc. degree in detection technology and automation equipment from Anhui Polytechnic University, China in 2004 and 2007, and the Ph. D. degree in control theory and control engineering from Donghua University, China in 2014. From July 2007 to December 2014, he was a teaching assistant and then a lecturer in Department of Mathematics, Anhui Polytechnic University, China. From June 2012 to September 2012, he was a research assistant in Department of Mechanical Engineering, the University of Hong Kong, China. From March 2013 to March 2014, he was a visiting scholar in Department of Information Systems and Computing, Brunel University, UK. He is currently a senior research fellow with School of Software and Electrical Engineering, Swinburne University of Technology, Australia. He is a Highly Cited Researcher according to Clarivate Analytics. He is a Senior Member of IEEE. He received the 2020 IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award, and the 2018 IET Control Theory and Applications Premium Award. He has published more than 80 papers in refereed international journals. He is an Associate Editor for Neurocomputing and IET Control Theory & Applications. He is also a very active reviewer for many international journals. His research interests include nonlinear stochastic control and filtering, as well as multi-agent systems and sensor networks. E-mail: dding@swin.edu.au ORCID iD: 0000-0001-7402-6682

  • Corresponding author: Q.-L. Han, Tel.: +61 3 9214 3808; Email: qhan@swin.edu.au
  • Received Date: 2021-04-15
  • Accepted Date: 2021-05-12
  • Available Online: 2021-06-11
  • The efficient utilization of computation and communication resources became a critical design issue in a wide range of networked systems due to the finite computation and processing capabilities of system components (e.g., sensor, controller) and shared network bandwidth. Event-triggered mechanisms (ETMs) are regarded as a major paradigm shift in resource-constrained applications compared to the classical time-triggered mechanisms, which allows a trade-off to be achieved between desired control/estimation performance and improved resource efficiency. In recent years, dynamic event-triggered mechanisms (DETMs) are emerging as a promising enabler to fulfill more resource-efficient and flexible design requirements. This paper provides a comprehensive review of the latest developments in dynamic event-triggered control and estimation for networked systems. Firstly, a unified event-triggered control and estimation framework is established, which empowers several fundamental issues associated with the construction and implementation of the desired ETM and controller/estimator to be systematically investigated. Secondly, the motivations of DETMs and their main features and benefits are outlined. Then, two typical classes of DETMs based on auxiliary dynamic variables (ADVs) and dynamic threshold parameters (DTPs) are elaborated. In addition, the main techniques of constructing ADVs and DTPs are classified, and their corresponding analysis and design methods are discussed. Furthermore, three application examples are provided to evaluate different ETMs and verify how and under what conditions DETMs are superior to their static and periodic counterparts. Finally, several challenging issues are envisioned to direct the future research.

     

  • 1We use the terms “event-triggered mechanism” and “event trigger” interchangeably throughout the paper whenever without causing confusion.
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