Networked Control Systems: A Survey of Trends and Techniques

Xian-Ming Zhang; Qing-Long Han; Xiaohua Ge; Derui Ding; Lei Ding; Dong Yue; Chen Peng

doi:10.1109/JAS.2019.1911651

Volume 7 Issue 1

Jan. 2020

IEEE/CAA Journal of Automatica Sinica

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Xian-Ming Zhang, Qing-Long Han, Xiaohua Ge, Derui Ding, Lei Ding, Dong Yue and Chen Peng, "Networked Control Systems: A Survey of Trends and Techniques," IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 1-17, Jan. 2020. doi: 10.1109/JAS.2019.1911651

Citation:

Xian-Ming Zhang, Qing-Long Han, Xiaohua Ge, Derui Ding, Lei Ding, Dong Yue and Chen Peng, "Networked Control Systems: A Survey of Trends and Techniques," IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 1-17, Jan. 2020. doi: 10.1109/JAS.2019.1911651

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Networked Control Systems: A Survey of Trends and Techniques

doi: 10.1109/JAS.2019.1911651

Funds: This work was supported in part by the Australian Research Council Discovery Project (DP160103567)

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Author Bio:
Xian-Ming Zhang (M’16-SM’18) received the M.Sc. degree in applied mathematics and the Ph.D. degree in control theory and engineering from Central South University, Changsha, China, in 1992 and 2006, respectively. In 1992, he joined Central South University, where he was an Associate Professor with the School of Mathematics and Statistics. From 2007 to 2014, he was a Post-Doctoral Research Fellow and a Lecturer with the School of Engineering and Technology, Central Queensland University, Rockhampton, QLD, Australia. From 2014 to 2016, he was a Lecturer with the Griffith School of Engineering, Griffith University, Gold Coast, QLD, Australia. In 2016, he joined the Swinburne University of Technology, Melbourne, VIC, Australia, where he is currently a Senior Lecturer with the School of Software and Electrical Engineering. His current research interests include H-infinity filtering, event-triggered control systems, networked control systems, neural networks, distributed systems, and time-delay systems. Dr. Zhang 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, and the IET Premium Award in 2016, jointly with Prof. Q.-L. Han. He is an Associate Editor of the Journal of the Franklin Institute, International Journal of Control, Automation, and Systems and the Neurocomputing, and he is an Editorial Board Member of Neural Computing and Applications

Qing-Long Han (M’09–SM’13-F’19) received the B.Sc. degree in Mathematics from Shandong Normal University, Jinan, China, in 1983, and the M.Sc. and Ph.D. degrees in Control Engineering and Electrical Engineering from East China University of Science and Technology, Shanghai, China, in 1992 and 1997, respectively. From September 1997 to December 1998, he was a Post-doctoral Researcher Fellow with the Laboratoire d’Automatique et d’Informatique Industielle (currently, Laboratoire d’Informatique et d’Automatique pour les Systémes), École Supérieure d’Ing’enieurs de Poitiers (currently, École Nationale Supérieure d’Ingénieurs de Poitiers), Université de Poitiers, France. From January 1999 to August 2001, he was a Research Assistant Professor with the Department of Mechanical and Industrial Engineering at Southern Illinois University at Edwardsville, USA. From September 2001 to December 2014, he was Laureate Professor, an Associate Dean (Research and Innovation) with the Higher Education Division, and the Founding Director of the Centre for Intelligent and Networked Systems at Central Queensland University, Australia. From December 2014 to May 2016, he was Deputy Dean (Research), with the Griffith Sciences, and a Professor with the Griffith School of Engineering, Griffith University, Australia. In May 2016, he joined Swinburne University of Technology, Australia, where he is currently Pro Vice-Chancellor (Research Quality) and a Distinguished Professor. In March 2010, he was appointed Chang Jiang (Yangtze River) Scholar Chair Professor by Ministry of Education, China. His research interests include networked control systems, multi-agent systems, time-delay systems, complex dynamical systems and neural networks. Professor Han is one of The World’s Most Influential Scientific Minds: 2014-2016, and 2018. He is a Highly Cited Researcher according to Clarivate Analytics (formerly Thomson Reuters). He is a Fellow of The Institution of Engineers Australia. He is an Associate Editor of several international journals, including the IEEE Transactions on Cybernetics, the IEEE Transactions on Industrial Electronics, the IEEE Transactions on Industrial Informatics, IEEE Industrial Electronics Magazine, the IEEE/CAA Journal of Automatica Sinica, Control Engineering Practice, and Information Sciences

Xiaohua Ge (M’18) received the B.Eng. degree in electronics and information engineering from Nanchang Hangkong University, Nanchang, China, in 2008, the M.Eng. degree in control theory and control engineering from Hangzhou Dianzi University, Hangzhou, China, in 2011, and the Ph.D. degree in computer engineering from Central Queensland University, Rockhampton, QLD, Australia, in 2014. From 2011 to 2013, he was a Research Assistant with the Centre for Intelligent and Networked Systems, Central Queensland University, Rockhampton, QLD, Australia, where he was a Research Fellow in 2014. From 2015 to 2017, he was a Research Fellow with the Griffith School of Engineering, Griffith University, Gold Coast, QLD, Australia. He is currently a Lecturer with the School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, VIC, Australia. His research interests include distributed estimation over sensor networks, distributed coordination in multi-agent systems, security and privacy preserving in cyber-physical systems

Derui Ding (M’16) received both the B.Sc. degree in Industry Engineering in 2004 and the M.Sc. degree in Detection Technology and Automation Equipment in 2007 from Anhui Polytechnic University, Wuhu, China, and the Ph.D. degree in Control Theory and Control Engineering in 2014 from Donghua University, Shanghai, China. From July 2007 to December 2014, he was a teaching assistant and then a lecturer in the Department of Mathematics, Anhui Polytechnic University, Wuhu, China. He is currently a senior research fellow with the School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, Australia. From June 2012 to September 2012, he was a research assistant in the Department of Mechanical Engineering, the University of Hong Kong, Hong Kong. From March 2013 to March 2014, he was a visiting scholar in the Department of Information Systems and Computing, Brunel University London, UK. His research interests include nonlinear stochastic control and filtering, as well as multi-agent systems and sensor networks. He has published around 40 papers in refereed international journals. Dr. Ding is serving as an Associate Editor for Neurocomputing. He is also a very active reviewer for many international journals

Lei Ding (M’18) received the B.Sc. degree in automation, and the M.Sc. and Ph.D. degrees in control theory and control engineering from Dalian Maritime University, Dalian, China, in 2007, 2009 and 2014, respectively. From November 2010 to November 2012, he was a visiting Ph.D. student sponsored by China Scholarship Council at the Centre for Intelligent and Networked Systems, Central Queensland University, Australia. From January 2015 to January 2016, he was a visiting Research Fellow at Western Sydney University, Australia. From May 2016 to January 2017, he was a Postdoctoral Associate at Wayne State University, USA. From February 2017 to March 2019, He worked as a Research Fellow at Swinburne University of Technology, Australia. In March 2019, he joined Nanjing University of Posts and Telecommunications, where he is currently a Professor with the Institute of Advanced Technology. His research interests include event-triggered control and distributed cooperative control of multi-agent systems and their applications to smart grids

Dong Yue (SM’08) received the Ph.D. degree in Control Science and Engineering from the South China University of Technology, Guangzhou, China, in 1995. He is currently a Changjiang Professor and Dean of Institute of Advanced Technology, Nanjing University of Posts and Telecommunications. His research interests include analysis and synthesis of networked control systems, multi-agent systems, optimal control of power systems, and internet of things. He is currently an Associate Editor of the IEEE Transactions on Industrial Informatics, the IEEE Transactions on Neural Networks and Learning Systems, Journal of The Franklin Institute, International Journal of Systems Science and the IEEE Control Systems Society Conference Editorial Board

Chen Peng (M’13–SM’15) received the Ph.D. degree in control theory and control engineering from the Chinese University of Mining Technology, Xuzhou, China, in 2002. From 2004 to 2005, he was a Research Associate with the University of Hong Kong, Hong Kong. From 2006 to 2007, he was a Visiting Scholar with the Queensland University of Technology, Brisbane, QLD, Australia. From 2011 to 2012, he was a Post-Doctoral Research Fellow with the Central Queensland University, Rockhampton, QLD, Australia. In 2012, he was appointed as an Eastern Scholar by the Municipal Commission of Education, Shanghai, China, and joined Shanghai University, Shanghai, where he is currently the Director of Centre of Networked Control Systems and a Distinguished Professor. In 2018, he was appointed as an Outstanding Academic Leader by the Municipal Commission of Science and Technology, Shanghai. His current research interests include networked control systems, distributed control systems, security control, and intelligent control systems. Prof. Peng was a recipient of the one of the Most Cited Chinese Researchers Award in Computer Science by Elsevier from 2014 to 2018. He is an Associate Editor of a number of international journals, including Information Sciences and Transactions of the Institute of Measurement and Control
Corresponding author: X.-M. Zhang, Q.-L. Han, X. Ge, and D. Ding are with the School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, VIC 3122, Australia (e-mail: xianmingzhang@swin.edu.au; qhan@swin.edu.au; xge@swin.edu.au; dding@swin.edu.au)
¹A function \begin{document}$\alpha(\cdot) $\end{document} is said to be of class \begin{document}${\cal{K}}_{\infty} $\end{document} if it is continuous, strictly increasing and satisfies \begin{document}$\lim_{s\rightarrow\infty}\alpha(s) = \infty $\end{document} and \begin{document}$\alpha(0) = 0 $\end{document}.
Received Date: 2019-05-31
Accepted Date: 2019-07-10

Available Online: 2019-07-12

Abstract

Abstract

Networked control systems are spatially distributed systems in which the communication between sensors, actuators, and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices, increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems, process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The ‘control over networks’ is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of ‘control over networks’, providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research.
- Event-triggered control,
- networked control systems,
- quantization control,
- sampled-data control,
- security control

FullText(HTML)

¹A function $\alpha(\cdot) $ is said to be of class ${\cal{K}}_{\infty} $ if it is continuous, strictly increasing and satisfies $\lim_{s\rightarrow\infty}\alpha(s) = \infty $ and $\alpha(0) = 0 $.

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Networked Control Systems: A Survey of Trends and Techniques

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