Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Cyber-physical systems (CPS) are engineered systems with built-in seamless integration of physical and cyber components. Fundamental developments in sensing, communication, control, and computing technologies endow CPS with flexibility, adaptability, scalability, and robustness. The availability and size of input-output data generated along with the control of CPS bring a unique opportunity for machine learning techniques to advance the theory of dynamical control systems, by learning control rules directly from data. Integration of input-output data into adaptive, robust, predictive, and distributed control policies holds the key to exploiting the potential of learning and optimisation in the CPS designs. There are several challenges related to sampling, transmission, synchronization, as well as associated cyber security when merging contemporary data-based and traditional model-based control techniques for CPS. The overarching goal of this special issue is to bring together innovative developments on the interface between learning, control, and optimisation targeting cyber-physical opportunities emerging from power, transportation, and manufacturing systems. Through a rigorous peer review process, three articles have been accepted, which are summarised below. In the study, "Learning-based distributed adaptive control of heterogeneous multi-agent systems with unknown leader dynamics", the authors develop a distributed adaptive tracking control method for heterogeneous multi-agent systems with unknown leader dynamics in a directed graph. In contrast to the reported leader-following consensus studies, the prior knowledge of the leader is supposed to be cognised by some or all of the followers, the situation that the leader's dynamics are totally unrecognised but can be learned for each individual follower is considered. A data-driven learning algorithm using the system's data is developed to reconstruct the unknown systems matrix. Then, an adaptive distributed dynamic compensator is exploited to provide the leader's state estimation in a directed graph. Afterwards, a dynamic output feedback control law for each agent is projected. Theoretical analysis shows that the proposed algorithms not only ensure that all followers can identify the unknown system matrix but also guarantee that the distributed output leader-following consensus control with heterogeneous dynamics is achieved without any global information. In the study, "Sampled-data synchronisation of singular Markovian jump system (SMJS): application to a DC motor model", the authors consider the sampled-data synchronisation problem for SMJSs subject to aperiodic sampled-data control. Firstly, by constructing mode-dependent one-sided loop-based Lyapunov functional (LBLF) and two-sided LBLF, two different stochastically admissible conditions are suggested for error SMJSs with aperiodic sampled-data. It is guaranteed that the slave system is stochastically synchronised to the master system on the basis of the proposed stochastically admissible conditions. Secondly, two corresponding mode-dependent aperiodic sampled-data controller design approaches are provided for error SMJSs based on two different conditions, respectively. Finally, the validity of these approaches is demonstrated by a DC motor model. It also demonstrated that the two-sided LBLF method possesses a larger upper bound of the sampling period than the one-sided LBLF method. In the study, "Predefined-time distributed event-triggered algorithms for resource allocation", the authors propose a predefined-time distributed algorithm and analyse its convergence by using the Lyapunov stability theory in which the local constraint is ensured by a differential projection operator. Thus, a predefined time is obtained using a time-varying time-based generator. In addition, to reduce the communication consumption between agents, the authors develop a static as well as a dynamic-based event-triggered control scheme, where the information broadcast only occurs at some discrete time instants. Moreover, the three proposed algorithms converge precisely to the global optimal solution. Besides, the Zeno behaviour is excluded in the above static and dynamic event-triggered mechanisms. The guest editors would like to thank the Editor-in-Chief of the IET Cyber-Physical Systems: Theory & Applications, Prof. Shiyan Hu, and the Editorial Office for their great support of our special issue. In addition, we thank all the authors who submitted their quality papers to this special issue, and special thanks go to all anonymous reviewers for their great efforts and time to accomplish their review tasks. Data sharing not applicable. Jian Sun is currently a professor at Beijing Institute of Technology, China. He received the bachelor's degree from the Department of Automation and Electric Engineering, Jilin Institute of Technology, Changchun, China, in 2001, the master's degree from the Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CAS), Changchun, in 2004, and the Ph.D. degree from the Institute of Automation, CAS, Beijing, China, in 2007. He was a Research Fellow with the Faculty of Advanced Technology, University of Glamorgan, Pontypridd, U.K., from 2008 to 2009. He was a Post-Doctoral Research Fellow with the Beijing Institute of Technology, Beijing, from 2007 to 2010. In 2010, he joined the School of Automation, Beijing Institute of Technology, where he has been a Professor since 2013. His current research interests include networked control systems, time-delay systems, and security of cyber-physical systems. He is also an Editorial Board Member of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, the Journal of Systems Science and Complexity, and Acta Automatica Sinica. Qing-Long Han is Pro Vice-Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology, Melbourne, Australia. He held various academic and management positions at Griffith University and Central Queensland University, Australia. He received the Ph.D. degree in Control Engineering from East China University of Science and Technology in 1997. He has been conducting research in the areas of networked control systems, cyber physical systems, time-delay systems, multi-agent systems, smart grids, offshore structure, unmanned surface vehicles, cyber security, and neural networks. Since 2001, as of 12 August 2021, he has authored or co-authored three hundred and thirty-nine (339) fully-refereed high quality journal articles including one hundred and seventy-six (176) articles in the most prestigious IEEE Transactions, and thirty-seven (37) articles in Automatica. He has also authored or co-authored one hundred and eighty-four (184) international leading conference papers, five (5) monographs, one (1) research-based book chapter, and edited four (4) conference proceedings and ten (10) special issues. His research work has been cited 32,886 times with an h-index of 102, an i10-index of 296 according to Google Scholar. He is a Highly Cited Researcher in the Essential Science Indicator (ESI) field of Engineering (2014–2017), in the ESI Cross-Field (2018) and in both the ESI fields of Engineering and Computer Science (2019–2020) by Clarivate Analytics (Thomson Reuters). He is one of Australia's Top 5 Lifetime Achievers (Research Superstars) in the discipline area of Engineering and Computer Science by The Australian's Research Magazine (2019-2020). He is one of Australia's Top 5 Researchers in Computer Science and Electronics by Guide2Research. 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 (SMC) 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 was the recipient of The 2020 IEEE SMC Society Best Associate Editor Award and The 2020 IEEE/CAA Journal of Automatica Sinica Outstanding Associate Editor Award. Professor Han is a Member of the Academia Europaea (The Academy of Europe). He is a Fellow of The Institute of Electrical and Electronic Engineers (IEEE) and a Fellow of The Institution of Engineers Australia. He has served as an AdCom Member of IEEE Industrial Electronics Society (IES), a Member of IEEE IES Fellows Committee, and Chair of IEEE IES Technical Committee on Network-based Control Systems. He has served as Co-Editor-in-Chief of IEEE Transactions on Industrial Informatics (2022–2024), Co-Editor of Australian Journal of Electrical & Electronics Engineering, an Associate Editor for 12 international journals including IEEE Transactions on Cybernetics, IEEE Industrial Electronics Magazine, IEEE/CAA Journal of Automatica Sinica, Control Engineering Practice, Information Sciences, and a Guest Editor for 13 Special Issues. Guo-Ping Liu is currently a chair professor with the Southern University of Science and Technology, China. He received the BEng and MEng degrees from Central South University of Technology (now Central South University, China) in 1982 and 1985, respectively, and the PhD degree from University of Manchester in the UK in 1992. He did the postdoctoral research in the University of York in 1992–1993. He worked as a research fellow with the University of Sheffield in 1994-1996. During 1996–2000, he was a senior engineer with GEC-Alsthom and ALSTOM, and then a principal engineer and a project leader with ABB ALSTOM Power. He was a senior lecturer with the University of Nottingham in 2000–2003, a visiting professor with the Chinese Academy of Sciences in 2001-2005 and with the Harbin Institute of Technology in 2008–2013, and a professor with the University of South Wales in 2004–2019 and with Wuhan University in 2019–2021. Prof Liu's research interests include networked control systems, multi-objective optimal control, nonlinear identification and control, and industrial advanced control applications. He has completed more than 70 research projects as a principal investigator. He is an author of 10 books, 2 edited books, over 330 journal papers and 320 conference papers, and has 14 patents, 34 software copyrights and 2 software products. He was awarded the Alexander von Humboldt Research Fellowship in 1992. He was named a Highly Cited Researcher by Thomson Reuters in 2014 and 2015, by Clarivate Analytics in 2016–2018, and by Elsevier in 2014–2020. He received the second prize of Chinese National Science and Technology Awards in 2008 and 2015. Prof. Liu was the general chair of the 2007 IEEE International Conference on Networking, Sensing and Control, the 2011 International Conference on Intelligent Control and Information Processing, and the 2012 UKACC International Conference on Control. He has served as an Editor-in-Chief of the International Journal of Automation and Computing in 2004–2021 and an Honorary Editor-in-Chief of the journal "Advances in Internet of Things" since 2011. He is a Fellow of IEEE, a Fellow of IET and a member of the Academy of Europe. Yajun Pan is currently a Professor in the Department of Mechanical Engineering at Dalhousie University, Canada. She received the B.E. degree in Mechanical Engineering from Yanshan University, P.R. China, in 1996, the M.E. degree in Mechanical Engineering from Zhejiang University, P.R. China, in 1999 and the Ph.D degree in Electrical and Computer Engineering from the National University of Singapore, in 2003. After receiving the Ph.D. degree, she was a post-doctoral fellow of CNRS in the Laboratoire d'Automatique de Grenoble, France from 2003 to 2004. In 2004, she held post-doctoral position in the department of Electrical and Computer Engineering at the University of Alberta, Canada. She is currently an Associate Editor of the IEEE Transactions on Industrial Electronics (2019 Present), IEEE Transactions on Cybernetics (2016-Present), and IEEE/ASME Transactions on Mechatronics (2015–2020). She has been the Associate Editor for the Journal of Franklin Institute (2007–2013), International Journal of Advanced Robotics Systems (2014–2018), and the International Journal of Information and Systems Sciences (2009–2017). She is the Editor of the special issue on Advances in Methods for Control over Networks for the Journal of Control Science and Engineering; and the guest editor for the special issue in Advanced Modelling and Control of Complex Mechatronic Systems with Nonlinearity and Uncertainty for IEEE Access (2017–2018). She is a Fellow of Engineering Institute of Canada (FEIC - 2021), a Fellow of the American Society of Mechanical Engineers (ASME - 2017), a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), a member of Canadian Society of Mechanical Engineering (CSME) and a Registered Professional Engineer in the Province of Nova Scotia, Canada. Dr. Pan was awarded the Research Excellence Award (Junior Category, Academic Year of 2008–2009) in the Faculty of Engineering, Dalhousie University. She has served as the evaluation group member for NSERC Discovery Grant (2017–2020) and also the selection committee member for NSERC RTI grant in 2016–2017. She has served as the Vice-President, Atlantic Region, for Canadian Society of Mechanical Engineering (CSME) from 2018–2020. Tao Yang is a Professor at the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University. He was an Assistant Professor at the Department of Electrical Engineering, University of North Texas, Denton, USA, from 2016–2019. He received the Ph.D. degree in electrical engineering from Washington State University in 2012. Between August 2012 and August 2014, he was an ACCESS Post-Doctoral Researcher with the ACCESS Linnaeus Centre, Royal Institute of Technology, Sweden. He then joined the Pacific Northwest National Laboratory as a postdoc, and was promoted to Scientist/Engineer II in 2015. His research interests include industrial artificial intelligence, integrated optimization and control, distributed control and optimization with applications to process industries, cyber physical systems, and networked control systems. He is an Associate Editor for IEEE Transactions on Control Systems Technology and IEEE/CAA Journal of Automatica Sinica. He currently is a member of the Technical Committee on Nonlinear Systems and Control, the Technical Committee on Networks and Communication Systems, and the Technical Committee on Smart Grids of the IEEE Control Systems Society, a member of the IEEE Control Systems Society Conference Editorial Board, and a member of the IFAC Technical Committee on Large Scale Complex Systems. He received Ralph E. Powe Junior Faculty Enhancement Award and Best Student Paper award (as an advisor) of the 14th IEEE International Conference on Control & Automation in 2018. Jiahu Qin is currently a Professor with the Department of Automation, University of Science and Technology of China, Hefei, China. He received the first Ph.D. degree in control science and engineering from the Harbin Institute of Technology, Harbin, China, in 2012, and the second Ph.D. degree in systems and control from the Australian National University, Canberra, ACT, Australia, in 2014. His current research interests include multi-agent systems, cyber-physical systems, and complex dynamical networks. Dr. Qin serves as the Deputy Director of Youth Committee of Chinese Association of Automation. He is currently an Associate Editor of IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, Journal of The Franklin Institute, Neurocomputing, Acta Automatica Sinica, IET Cyber-Physical Systems: Theory & Applications, etc. He is a recipient of the 2017 IEEE IES (Industrial Electronics Society) Best Conference Paper Award.