Ben M. Chen, Professor & Provost’s Chair, Department of Electrical and Computer Engineering, National University of Singapore

Development of Intelligent Unmanned Aerial Systems and Their Applications

In this talk, we aim to report some advanced unmanned aerial systems (UAS) recently developed by the Unmanned Systems Research Group at the National University of Singapore. Attention is particularly paid to UAS, which is capable of navigating through in cluttered indoor and outdoor GPS-denied environments, such as hostile buildings, sewer tunnels, radiation contaminated areas and inside forests. Topics under studied include dynamic modeling of an unmanned helicopter, advanced flight control system design, multi-sensory data fusion, real-time simultaneous localization and mapping, and dynamic path planning in unknown environments. We will particularly showcase the development of an unconventional hybrid aircraft, which has the capability of taking off and landing vertically, and transiting to a fixed-wing mode for fast cruise flight. We will also take this opportunity to present some techniques that we have recently developed for the 2017 International Micro Air Vehicles Competition, held in Toulouse, France, September 2017. The real industrial applications of the drones for deep tunnel inspection and warehouse inventory counting will be highlighted in the talk as well.

Short Bio: Ben M. Chen is currently a Professor and Provost’s Chair in the Department of Electrical and Computer Engineering, National University of Singapore. He is also serving as the Director of NUS ECE Control, Intelligent Systems and Robotics Area. His current research interests are in unmanned systems, robust control, control applications, and financial market modeling.
Dr. Chen is an IEEE Fellow. He has published more than 400 journal and conference articles, and a dozen research monographs including Robust and H∞ Control (Springer, New York, 2000), Hard Disk Drive Servo Systems (Springer, 1st Edition, 2002; 2nd Edition, New York, 2006), Linear Systems Theory (Birkhäuser, Boston, 2004), Unmanned Rotorcraft Systems (Springer, New York, 2011), and Stock Market Modeling and Forecasting (Springer, New York, 2013). He had served on the editorial boards of several international journals including IEEE Transactions on Automatic Control, Systems & Control Letters, and Automatica. He currently serves as an Editor-in-Chief of Unmanned Systems.
Dr. Chen has received a number of research awards nationally and internationally. His research team has actively participated in international UAV competitions, and won quite a few championship awards in the contests, including very recent ones – the indoor competition champion and the outdoor competition champion at the 2017 International Micro Air Vehicles Competition, held in Toulouse, France, September 2017.

Lihua Xie, Professor, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

Cooperative Localization and Control of Multi-robot Systems

Multiple cooperating robots are able to complete many tasks more efficiently and reliably than one robot alone. Multi-robot systems involve multi-disciplinary research ranging from platform design, sensing and perception, data fusion, localization, task assignment, path planning, communication and networking, control and coordination, and fleet management. There has been a lot of research on multi-agent systems in recent years. However, there exists a significant gap between theoretical research and practice. In this talk, we shall focus on cooperative localization and control of multi-robot systems in GPS denied environments. In particular, we shall introduce recently developed distance based cooperative localization including consensus based approach and graph optimization based approach, leveraging on UWB technologies. We shall also discuss simultaneous relative localization and formation control of multi-robot systems, and demonstrate their applications in unmanned ground and aerial vehicles.

Short Bio: Lihua Xie received the B.E. and M.E. degrees in electrical engineering from Nanjing University of Science and Technology in 1983 and 1986, respectively, and the Ph.D. degree in electrical engineering from the University of Newcastle, Australia, in 1992. He was a faculty with the Department of Automatic Control, Nanjing University of Science and Technology from 1986 to 1989. Since 1992, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, where he is currently a professor and the Director of the Delta-NTU Corporate Laboratory for Cyber-Physical Systems. He served as the Head of Division of Control and Instrumentation from July 2011 to June 2014. His research areas include robust control, networked control, compressive sensing, localization and unmanned systems. He has been listed as a highly cited researcher by Thomson Routers and Clarivate Analytics since 2014. He is currently an Editor-in-Chief of Unmanned Systems and Associate Editor of IEEE Transactions on Control of Network Systems. He has served as an Editor of IET Book Series on Control and Associate Editor of IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, Automatica, IEEE Transactions on Circuits and Systems-II, etc. He is Fellow of IEEE, Fellow of IFAC, and an elected member of the Board of Governors of IEEE Control System Society.

Zhiyong Chen, Professor, School of Electrical Engineering and Computing, The University of Newcastle , Australia

Natural Oscillation Gait in Humanoid Biped Locomotion

Abstract: Biped locomotion is complex to analyze in general. Most of the models in literature for biped locomotion utilize hybrid dynamics.This makes the kinematics of the model simple to understand. However,it makes the model difficult to analyze in the presence of discontinuous terms in its differential equations. In this talk, we discuss a continuous-time mathematical model for biped robots,modelling the discontinuities in impact with a nonlinear function.Natural oscillation is defined as a free response under damping compensation to achieve persistent oscillation. The phenomenon of natural oscillation was previously exploited in the linear dynamics of multi-segmental locomotor, and it is now extended to this continuous-time biped locomotion model with the contact force from the ground modelled as a nonlinear bump function. The idea of natural oscillation is preceded by a complete framework on analysis and entrainment control. The research would ensure that these natural oscillations are responsible for forward locomotion of biped robots under certain conditions. The locomotion profile of the bipeds further validates the model that the velocity achieved through the natural oscillation is comparable to human jogging speeds, when practical constraints are enforced.

Bio: Zhiyong Chen received his Bachelor degree from the Department of Automation, University of Science and Technology of China in 2000. He received his M.Phil. and Ph.D. degrees from the Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, in 2002 and 2005, respectively. He worked as a Research Associate at the University of Virginia during 2005-2006. He joined the School of Electrical Engineering and Computing, the University of Newcastle, Australia in 2006 where he is currently a Full Professor.He was elected to Changjiang Scholar Chair Professorship with Central South University in 2016. He is also holding a Chair Professorship with Huazhong University of Science and Technology. He is an author of over 80 journal papers and one textbook. He was/is a Chief/Principal Investigator of three projects supported by Australian Research Council and two major projects supported by National Natural Science Foundation of China. He was/is an Associate Editor for many top tier journals including IEEE Transactions on Automatic Control,IEEE Transactions on Cybernetics, IFAC Mechatronics, Systems and Control Letters, and International Journal of Robust and Nonlinear Control. He received the Best PhD Thesis Award of the Year 2015 from the Faculty of Engineering, CUHK. He is the recipient of National Natural Science Award of China (second prize) in 2010, and several international conference best paper awards.

Jian Huang, Professor, School of Automation, Huazhong University of Science and Technology, China

Control of Walking-Aid Robot Based on Motion Intention/State Sensing

Abstract: The mobility of elderly degrades with age, which affects not only their daily life, but also the life quality and causes dependence of other in their daily life. The walking-aid robot which applies robotic technologies can help the elderly to restore the ability of walking, get the chance of independent and improve the quality of their life, which are very important to the rehabilitation care system of forthcoming elderly society.
Recognizing the user’s walking intention plays an important role in the motion control of walking-aid robots. To quantitatively describe the user’s walking intention, a concept called “intentional direction (ITD)” is proposed. Both the state model and the observation model of ITD are obtained by enumerating the possible walking modes and analyzing the relationship between the human–robot interaction force and the walking intention. The user’s walking intention can be online estimated using the filtering techniques. Based on the estimated intention, a new admittance motion control scheme is proposed for the walking-aid robot.
The walking state monitoring is also indispensable during using the robot-aided walking. We verified the existence of human-robot coordination state in the process of using a walking-aid robot during walking. A new walking state monitoring method is proposed by using the Principal Component Analysis (PCA). The abnormal or emergency walking state is promptly detected if the new sample data is found to deviate from an off-line PCA model, which is generated from plentiful normal walking data of different subjects. Further, a state diagnosis algorithm based on the contribution plot is also developed for the walking state recognition and diagnosis. In this way, typical abnormal states like the leg restrictions can be distinguished from the emergency states including falls and the stumbling.
The effectiveness of proposed method is validated by experiments. The result shows that the user feels more natural and comfortable when our intention-based admittance control is applied. Better recognition rate and real-time performance of the walking-state monitoring method is also verified by comparing with conventional Center of Pressure (COP)-based monitoring method.

Bio: Jian Huang graduated from Huazhong University of Science and Technology (HUST), China in 1997 and received the Master of Engineering degree from HUST in 2000. He received his Ph.D from HUST in 2005. From 2006 to 2008, he was a postdoctoral researcher in the Department of Micro-Nano System Engineering and Department of Mechano-Informatics and Systems, Nagoya University, Japan. In 2015, he was a research fellow in Nagoya University supported by JSPS invitation fellowship. He is currently a full professor with the School of Automation, HUST. He is also a guest professor in Nagoya University of Japan and University Paris-Est Créteil (UPEC) of France. His main research interests include rehabilitation robot, robotic assembly, networked control systems and bioinformatics.
He is an IEEE Senior Member and has published more than 170 papers (including 16 research articles in several IEEE Transactions and more than 50 conference papers in many IEEE conferences). Currently he serves as the editor of ROBOMECH Journal – Springer.
He has got 12 authorized patents, the grand prize of science and technology award of China General Chamber of Commerce and was awarded golden medal at Geneva Inventions in 2017.

Dong Yue, Professor, Institute of Advanced Technology and College of Automation, Nanjing University of Posts and Telecommunications

Event-triggered control design and its applications

Bio: Dong Yue received the Ph.D. degree from the South China University of Technology, Guangzhou, China, in 1995.He is currently a professor and dean of the Institute of Advanced Technology and College of Automation, Nanjing University of Posts and Telecommunications and also a Changjiang Professor with the Department of Control Science and Engineering, Huazhong University of Science and Technology. He is currently an Associate Editor of the IEEE Control Systems Society Conference Editorial Board and also an Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems, the Journal of the Franklin Institute and the International Journal of Systems Science. Up to now, he has published more than 100 papers in international journals. His research interests include analysis and synthesis of networked control systems, multi-agent systems, optimal control of power systems, and internet of things.

Qing-Long Han, Distinguished Professor, FIEAust, Swinburne University of Technology, Australia

Distributed Coordinated Control and Filtering of Networked Systems

Abstract: Recent advances in networking technologies, especially wireless networks, generate a new paradigm of control and filtering for industrial systems via networks. Traditionally, such systems are controlled and estimated by independent networks, which are designed with enough bandwidth and resources. In network environments, shared wired and wireless networks are utilized to connect industrial systems and controllers/filters. In this framework, bandwidth and resource constraints should be taken into account in controller/filter design, and real-time becomes increasingly important to control and filtering. This keynote talk will provide a timely discussion on technical trends and challenges of distributed coordinated control and filtering for networked systems.

Bio: Qing-Long Han received Ph.D. degree in Control Engineering and Electrical Engineering from East China University of Science and Technology, Shanghai, China, in 1997. From September 1997 to December 1998, he was a Post-doctoral Researcher Fellow with the Laboratoire d’Auomatique et d’Informatique Industrielle (LAII) (currently, Laboratoire d’Informatique et d’Automatique pour les Systèmes, LIAS), École Supérieure d’Ingénieurs de Poitiers (ESIP) (currently, École Nationale Supérieure d’Ingénieurs de Poitiers (ENSIP)), 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, 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. He is also the Director of Centre for Networked Control Systems with the School of Mechatronic Engineering and Automation, Shanghai University, China. In March 2010, he was appointed Chang Jiang (Yangtze River) Scholar Chair Professor by Ministry of Education, China.
Professor Han has been conducting research in the field of Control Theory and Control Engineering. He has published over three hundred and sixty (360) fully-refereed papers in prestigious journals and leading conferences, two research-based books (monographs), one research-based book chapter, and edited three conference proceedings and four special issues. In particular, since 2001, he has published one hundred and ninety-eight (198) fully-refereed high quality journal articles. Among these articles, twenty-five (25) articles are published in Automatica, and fourteen (14) articles are published in IEEE Transactions on Automatic Control (the two best journals in the area of automatic control) and seventy-eight (78) articles are published in the most prestigious IEEE Transactions.
As of April 1, 2018, Professor Han’s research work has been cited 15466 times with h-index of 65, i10-index of 173 according to Google Scholar, 11841 times with h-index of 56 according to SCOPUS, and 9617 times with h-index of 53 according to Clarivate Analytics (formerly Thomson Reuters) Web of Science Core Collection. The Essential Science Indicator’s (ESI) Report on March 15, 2018, which covers the period from January 2007 to December 2017, indicated that he has 27 Highly Cited Papers.
Prof. Han is one of The World’s Most Influential Scientific Minds: 2014-2016 and is a Highly Cited Researcher in Engineering according to Thomson Reuters. He is a Fellow of The Institution of Engineers Australia. He is an Associate Editor of a number of international journals including IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Cybernetics, and Information Sciences. His research interests include networked control systems, time-delay systems, multi-agent systems, neural networks and complex dynamical systems.

Chun-Yi Su, Professor, Concordia University, Canada

Modeling and Control of Hysteresis Nonlinearities in Smart Actuators: Magnetostrictive Actuator Case

Abstract: Magnetostrictive actuators featuring high energy densities, large strokes and fast responses are playing an increasingly important role in micro/nano-positioning applications. However, such actuators with different input frequencies and mechanical loads exhibit complex dynamics and hysteretic behaviors, posing a great challenge on applications of the actuators. To this end, a comprehensive model is firstly developed. However, in the controller development the use of an estimated hysteresis model in deriving the inverse compensator would yield some degree of hysteresis compensation error. To accommodate such a compensation error, an analytical expression of the inverse compensation error is derived. Then, a prescribed adaptive control method is developed to suppress the compensation error and simultaneously guaranteeing global stability of the closed loop system with a prescribed transient and steady-state performance of the tracking error. The effectiveness of the proposed control scheme is validated on the magnetostrictive- actuated experimental platform.

Bio: Dr. Chun-Yi Su received his Ph.D. degrees in control engineering from South China University of Technology in 1990. After a seven-year stint at the University of Victoria, he joined Concordia University in 1998, where he is currently a Professor of Mechanical and Industrial Engineering and holder of Concordia University Research Chair in Control. He has also held several short-time visiting positions including a Chang Jiang Chair Professorship from China and JSPS Invitation Fellowship from Japan. His research covers control theory and its applications to various mechanical systems, with a focus on control of systems involving hysteresis nonlinearities. He is the author or co-author of over 400 publications, which have appeared in journals, as book chapters and in conference proceedings. In addition to his academic activities, he has worked extensively with industrial organizations on various projects.
Dr. Su has been an Associate Editor of IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, Mechatronics, Control Engineering Practice, and several other journals. He has served as Chair/Co-Chair for numerous international conferences.

Kok-Meng Lee, Professor, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, U.S.A

Physical Field-based Machine Perception for Direct Sensing and Control of Robotic, Automation and Mechatronic Systems

Abstract: Traditional sensors and light-based vision systems have led to significant advancement in robotics, automation and mechatronics (RAM), while showing important limitations in challenging environments where point-measurements and lumped-parameter models are inadequate to characterize the system behaviors. This talk presents methods to develop physical field-based sensing and perception systems (SPS) to facilitate autonomous machines capable of evolving with more and more ‘smart functions’ that ultimately make the process a self-improved system. The SPS use the existing physical fields in the RAM system as an alternative or a complement to visible light (commonly assumed as the medium in conventional machine vision). Selected applications include magnetic, electric, thermal and mechanic fields in intelligent RAM and in nature to help illustrate the impacts of physical field-based SPS in our rapidly changing world. As will be illustrated, physical fields that exist in nature, human and manmade systems can be reconstructed from limited measurements to infer motion variables for guiding navigation and/or identify system properties of a distributed-parameter system to control its system behaviors; thus, their creative uses can eliminate costly, complicated external measurement systems.

Bio: Dr. Kok-Meng Lee received his S. M. and Ph. D. degrees in mechanical engineering from the Massachusetts Institute of Technology in 1982 and 1985 respectively. Since 1985, Dr. Lee has been a faculty with the George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. Currently, he is Professor of Mechanical Engineering at Georgia Tech and is Distinguished Professor with the State Key Laboratory of Digital Manufacturing Equipment and Technology at Huazhong University of Science and Technology under the National Recruitment Program of Global Experts. He was also honored as Pao Yu-Kong Chair Professor at Zhejiang University.  His research interests include system dynamics/control, robotics, automation, machine vision, and mechatronics. Dr. Lee is a fellow of IEEE and ASME.  Recognitions of his research contributions include the NSF Presidential Young Investigator (PYI) Award, Sigma Xi Junior Faculty Award, International Hall of Fame New Technology Award, Woodruff Faculty Fellow, three best paper awards and ten U. S., Canada and European patents.  He is also recognized as advisor for nine Best Student Paper and Thesis Awards.
Dr. Lee is founding Editor-in-Chief for the Springer International Journal on Intelligent Robotics and Applications. Prior to this appointment, he served as Editor-in-Chief (2008-2013) and Technical Editor (1995-1999) for the IEEE/ASME Transactions on Mechatronics, Associate Editor for IEEE Robotics and Automation Society Magazine (1994-1996), IEEE Transactions on Robotics and Automation (1994-1998) and IEEE Transactions on Automation Science and Engineering (2003-2005). He was ICRA Local Chair (1993), IEEE/ASME AIM General Co-Chair (1997) and General Chair (1999) and as ASME Liaison for IEEE/ASME AIM (1999-2013, 2017-persent).

Yuanqing Xia, Professor, Beijing Institute of Technology, China

Compound Control Methodology for Flight Vehicles

Abstract: Flight vehicle includes aircraft, spacecraft, rocket and missile, which are operated for disparate missions. In the past decades, study on high precision attitude control for single flight vehicle and multiple flight vehicle systems (MFVS) has become a very active and exciting research field because of the important theoretical significance and broad practical applications. However, the current trend for single spacecraft is to design high-performance algorithms that rely on only some structured system errors in the absence of exact math model, simultaneously, the tendency for MFVS is to design distributed algorithms that utilizing only local interaction to achieve global group behavior in complex networks. In this talk, we shall focus on the finite-time control of attitude stabilization, attitude tracking for single flight vehicle, and finite-time control of attitude synchronization, formation reconfiguration for MFVS in complex networks. In particular, by combining sliding mode control, adaptive control and active disturbance rejection control, some compound control methods are developed for flight vehicles. The designed compound control methodologies provide finite-time convergence, robustness, faster, higher control precision, and they satisfy the high demand of control accuracy requirement in the actual flight missions.

Bio: Yuanqing Xia received his M.S. degree in Fundamental Mathematics from Anhui University, China, in 1998 and his Ph.D. degree in Control Theory and Control Engineering from Beijing University of Aeronautics and Astronautics, Beijing, China, in 2001. During January 2002–November 2003, he was a Postdoctoral Research Associate in the Institute of Systems Science, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, China. From November 2003 to February 2004, he was with the National University of Singapore as a Research Fellow. From February 2004 to February 2006, he was with the University of Glamorgan, Pontypridd, U.K., as a Research Fellow. From February 2007 to June 2008, he was a Guest Professor with Innsbruck Medical University, Innsbruck, Austria. Since July 2004, he has been with the School of Automation, Beijing Institute of Technology, Beijing, first as an Associate Professor, then, since 2008, as a Professor. And in 2012, he was appointed as Xu Teli Distinguished Professor at the Beijing Institute of Technology, then in 2016, as Chair Professor. In 2012, he obtained the National Science Foundation for Distinguished Young Scholars of China, and in 2016, he was honored as the Yangtze River Scholar Distinguished Professor and was supported by National High Level Talents Special Support Plan (“Million People Plan”) by the Organization Department of the CPC Central Committee. He is now the dean of School of Automation, Beijing Institute of Technology.
His current research interests are in the fields of networked control systems, robust control and signal processing, active disturbance rejection control and flight control. He has published eight monographs in Springer, John Wiley and CRC, and more than 100 papers in international scientific journals. He obtained the Second Award of the Beijing Municipal Science and Technology (No. 1) in 2010 and 2015, the Second National Award for Science and Technology (No. 2) in 2011, and the Second Natural Science Award of the Ministry of Education (No. 1) in 2012.