Youmin Zhang, Professor, Concordia University, Canada
Biography: Youmin Zhang received the B.S., M.S., and Ph.D. degrees from Northwestern Polytechnical University, Xi’an, China, in 1983, 1986, and 1995, respectively. He is currently a Professor with the Department of Mechanical, Industrial and Aerospace Engineering and the Concordia Institute of Aerospace Design and Innovation, Concordia University, Montreal, Quebec, Canada. His current research interests include condition monitoring, health management, Fault Detection and Diagnosis (FDD), and Fault-Tolerant Control (FTC), cooperative Guidance, Navigation, and Control (GNC) of single and multiple unmanned aerial/space/ground/surface vehicles and their applications to forest fires, pipelines, power lines, environment, natural resources and natural disasters monitoring, detection, and protection by combining with remote sensing techniques; dynamic systems modeling, estimation, identification, advanced control techniques and signal processing techniques for diagnosis, prognosis, and health management of safety-critical systems, renewable energy systems and smart grids, and intelligent manufacturing processes. He has authored 4 books, over 500 highly cited journal and conference papers, and book chapters. He is a Fellow of Canadian Society of Mechanical Engineering (CSME), a Senior Member of the American Institute of Aeronautics and Astronautics (AIAA) and the Institute of Electrical and Electronics Engineers (IEEE), and a member of the Technical Committee for several international and national scientific societies. He has been invited to deliver plenary and tutorial talks at international conferences/workshops and research seminars worldwide for over 100 times. He is an Editor-in-Chief, an Editor-at-Large, an Editorial Board Member, and Associate Editor of several international journals. He has served as General Chair, Program Chair, Program Vice Chair, and Advisory, Organizing Committee Member of several international conferences or organizations. In view of his outstanding research works, he has been awarded as a Concordia University Research Fellow Award in 2018 in the Strategic Research Cluster ‘Technology, Industry and the Environment’. More detailed information can be found at http://users.encs.concordia.ca/~ymzhang/.
Title: Challenges and New Developments on Fault Detection and Diagnosis (FDD), Fault-Tolerant Control (FTC), and Fault-Tolerant Cooperative Control (FTCC) of Unmanned Systems towards Practical Applications
Abstract: Although the concepts and developments on fault detection and diagnosis (FDD) and fault-tolerant control (FTC) have been progressively and extensively investigated worldwide since the 1970’s and 1980’s, respectively, the two recent catastrophic accidents induced by the crashes of two Boeing 737 MAX8 airplanes have highlighted again the necessity and urgency for FDD and FTC research & development and their industrial applications. On the other hand, benefited from technical advances in materials, mechatronics, communication, computation, control, sensors, actuators and new/smart designs, Unmanned Aerial Vehicles (UAVs) are gaining more and more attention and rapid development during the last a few years due to their relatively easy and cost-effective uses in various application tasks such as surveillance, sensing, search and rescue, agriculture, forest, environment, pipelines, powerlines, military and security applications. In this talk, brief overall view on the challenges and latest developments on Guidance, Navigation, and Control (GNC) of UAVs integrating with Remote Sensing (RS) techniques for autonomous, efficient and reliable applications to forest and environment monitoring and fires/damages/risks detection will be presented first, then some of new developments and current research works being carried out at presenter’s group will be introduced as the second part of the presentation. In particular, new developments on FDD, FTC, and Fault-Tolerant Cooperative Control (FTCC) techniques towards autonomous and reliable applications to the above-mentioned tasks based on the use of UAVs and also in wind farm as well as smart grids. New technical developments for efficient and reliable detection of fires/damages/risks based on remotely sensed signals/images from onboard UAVs will also be presented.
Quan Pan, Professor, Northwestern Polytechnical University, China
Biography: Pan Quan was born in Shanghai in 1961. He got Bachelor Degree from Huazhong Institute of Technology in Wuhan in 1991, Master Degree and PhD from Automatic College of Northwestern Polytechnical University (NPU) in Xi’an in 1991 and 1997. His research interests are Safety Assessment for Autonomous UAS, Target tracking, Information fusion, Hybrid system estimation theory, Image processing and etc. He is the Member of IEEE, the Member of International Society of Information Fusion (ISIF), the Member of Board of Chinese Association of Automation. He was the Duty Dean of Graduate School of NPU from 1996~2002, He is the Dean of Automatic School of NPU from 2009, the Director of the key Laboratory of Information Fusion Technology，Ministry of Education of China, the Professor of NPU from 1997. He has published 12 books, 100 international journal papers and 100 international conference papers.
Title: Safety Assessment for Autonomous Unmanned Aircraft System
Abstract: With the increasing demand for drones in the military and civilian fields and the further opening of airspace, air traffic safety under the existing air traffic control system will face major challenges.
UAV autonomous flight safety technology, mainly featured by the Sense and Avoid, is an important guarantee for airspace and air traffic safety. As a technology that restricts and integrates policy rules and technology research, UAV autonomous flight safety is also at the forefront of current international drone technology research. The report sorts out the main safety threats in the airspace integration process of UAVs. Based on this, the autonomous flight safety of UAVs is defined and modeled, and a complete evaluation framework and safety level classification of UAV autonomous flight safety is formed. Finally, based on the proposed UAV safety assessment system, it puts forward some thoughts and suggestions on the development of UAV technology and system construction.
Jihong Zhu, Professor, Tsinghua University, China
Biography: Jihong Zhu graduated from Jiangsu University of Science and Technology in 1990. He got the Ph.D. degree from Nanjing University of Science and Technology in 1995. He spent four years, 1996–1997 in Nanjing University of Aeronautics and Astronautics, 1998–1999 in Tsinghua University as a post-doctoral fellow. Now he is a professor in the Department of Computer Science and Technology in Tsinghua University. Over forty of his papers have been published. His academic interests are Robust Control and Filter of Nondefinite System and Flight Control.
Lung-Jieh Yang, Professor, Tamkang University
Biography: Lung-Jieh Yang received Ph.D. from Institute of Applied Mechanics, National Taiwan University in 1997 and is currently a professor of Mechanical Engineering at Tamkang University. He serves as the editor-in-chief of Journal of Applied Science and Engineering (ISSN 1560-6686) since 2008. He is the former department chair of Mechanical Engineering and the director of Instrument & Experiment Center of Tamkang University. He published over 60 journal papers, 10 patents and 2 books in the areas of MEMSand FWMAVs. Prof. Yang is also one of the Vice Presidentsof ISIUS and the host of ICIUS 2017 in Tamsui.
Title: Lift Improvement on the Membrane-Type Flapping Wing
Abstract: There are almost 20 years of development of flapping wing micro-air-vehicles (FWMAVs) since Caltech’s Microbat. Thanks to the MEMS devices, miniaturization of actuators and embedded microprocessor integration, people can feasiblyperform a 10-15 min real flight of FWMAVs with even on-board image taking and autonomous control. People also got impression about the low power consumption of FWMAVs. Before the next battery revolution with larger power density, one way to keep improving the flight endurance of FWMAVs is to optimize the wing design with high lift-to-weight ratio.
The traditional flapping wing is composed of a polymer membrane strengthen by carbon-fiber ribs. In this talk the Tamkang’s Golden Snitch is firstly exemplified to discuss the 4 factors which influence the lift, thrust and power. These 4 factors are (1) the strengthened leading edge, (2) rib location, (3) membrane material and (4) membrane thickness.
Biomimetic study attracts attention recently and also encourages us to mimic bird or insect wings. Among them the corrugated membrane wing is a master piece and has at least 3 advantages as (1) easy to be folded in the small pupa space; (2) aerodynamic equivalent to the similar solid airfoil with thickness; and (3)the better span-wise stiffness good to fluid-structure interaction (FSI). Therefore in this talk the fabrication and wind tunnel testing of the corrugated membrane wings will be discussed.
Finally a dimensionless stiffness parameter will be introducedto compare the aerodynamic difference between the traditional membrane wing and the corrugated membrane wing in an overall manner.
Zhijun Li, Professor, University of Science and Technology of China, China
Biography: Zhijun Li received the Ph.D. degree in mechatronics, Shanghai Jiao Tong University, P. R. China, in 2002. From 2003 to 2005, he was a postdoctoral fellow in Department of Mechanical Engineering and Intelligent systems, The University of Electro-Communications, Tokyo, Japan. From 2005 to 2006, he was a research fellow in the Department of Electrical and Computer Engineering, National University of Singapore, and Nanyang Technological University, Singapore. Since 2017, he is a Professor in Department of Automation, University of Science and Technology of China. He was supported by China National Ten-thousand Talents Program (China 2018), and received the prestigious award of National Distinguished Young Scholar (NSFC 2016), and Distinguished Young Scientist Award (CAA 2017), Distinguished Lecturer of IEEE Robotics and Automation Society(2018), Best Associate Editor Award (IEEE SMC) Toshio Fukuda Best Mechatronics Award (ICARM 2017), etc.. From 2016, he has been the founders and Co-Chairs of Technical Committee on Bio-mechatronics and Bio-robotics Systems (IEEE SMC), and Technical Committee on Neuro-Robotics Systems (IEEE RAS). He is serving as an Editor-at-large of Journal of Intelligent & Robotic Systems, and Associate Editors of several IEEE Transactions. He was the founder of IEEE Conference on Advanced Robotics and Mechatronics (IEEE ARM). He was the General Chair and Program Chair of 2016-2019 IEEE Conference on Advanced Robotics and Mechatronics, respectively. Dr. Li’s current research interests include service robotics, teleoperation systems, nonlinear control, neural network optimization, etc.
Title: Development of Key Technology for Human Cooperative Wearable robots and Its Applications
Abstract: The development of human cooperative robotic systems capable of sharing with humans the load of heavy tasks has been one of the primary objectives in robotics research. At present, in order to fulfill such an objective, a strong interest in the robotics community is collected by the so-called wearable robots, a class of robotics systems that are worn and directly controlled by the human operator. Wearable robots, together with powered orthoses that exploit robotic components and control strategies, can represent an immediate resource also for allowing humans to restore manipulation and/or walking functionalities. The present talks deals with wearable robotics systems capable of providing different levels of functional and/or operational augmentation to the human beings for specific functions or tasks. Prostheses, powered orthoses, and exoskeletons are described for upper limb, lower limb, and whole body structures. State-of-theart devices together with their functionalities and main components are presented for each class of wearable system. Critical design issues and open research aspects are reported.
Xin Xu, Professor, National University of Defense Technology, China
Biography: Dr. Xin Xu received the B.S. degree in electrical engineering from the Department of Automatic Control, National University of Defense Technology (NUDT), Changsha, China, in 1996 and the Ph.D. degree in control science and engineering from the College of Mechatronics and Automation, NUDT, in 2002. He has been a Visiting Professor with Hong Kong Polytechnic University, Hong Kong, the University of Alberta, Edmonton, AB, Canada, the University of Guelph, Guelph, ON, Canada, and the University of Strathclyde, Glasgow, U.K. He is currently a Professor with the College of Mechatronics and Automation, NUDT, China. He has co-authored over 160 papers in international journals and conferences, and co-authored four books. His current research interests include intelligent control, reinforcement learning, approximate dynamic programming, machine learning, robotics, and autonomous vehicles. Dr. Xin Xu was a recipient of the Fork Ying Tong Youth Teacher Fund of China in 2008 and the 2nd class National Natural Science Award of China, in 2012. He serves as the Co-Editor-in-Chief of the Journal of Intelligent Learning Systems and Applications and the Associate Editor-in-Chief of CAAI Transactions on Intelligent Technology (Elsevier). He is an Associate Editor of Information Sciences, Intelligent Automation and Soft Computing, and Acta Automatica Sinica. He served as the Guest Editor of the IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, the International Journal of Adaptive Control and Signal Processing, and International Journal of Social Robotics. He is a member of the IEEE CIS Technical Committee on Approximate Dynamic Programming and Reinforcement Learning and the IEEE RAS Technical Committee on Robot Learning.
Title: Recent Advances in Learning Control for Unmanned Systems
Abstract: Motivated by the main challenges due to real-time and high-precision requirements for motion control in unmanned systems, this report is to study the frameworks of past and recent developed learning control techniques for motion control of unmanned systems. The difference and relationship between learning control and traditional model-based control are primarily discussed. Special attention is focused on the designed approaches resorting to the iterative learning control (ILC), imitation learning (IML), and reinforcement learning (RL). For these frameworks, the methodologies and rationale adopted are analyzed, categories and achievements with literature reviews are listed, the pros and cons validated in applications are discussed. Finally, future challenging directions with a number of open problems are suggested.
Mou Chen, Professor, Nanjing University of Aeronautics and Astronautics, China
Biography: Mou Chen is now a professor and vice Dean of the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. He received the BSc degree and the PhD degree in Nanjing University of Aeronautics and Astronautics. He was awarded by the National Science Fund for Distinguished Young Scholars in 2018 and was elected to the Program for New Century Excellent Talents in University of Ministry of Education of China in 2011. He visited the Loughborough University, UK, from November 2007 to February 2008. He was a postdoctoral fellow in the National University of Singapore, Singapore, from June 2008 to September 2009. He was a senior research fellow in the University of Adelaide, Australia, from May 2014 to November 2014. He has actively served in the editorial boards of a number of international journals as an associate editor, including IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Access, Neurocomputing, International Journal of Advanced Robotic Systems, Chinese Journal of Aeronautics, SCIENCE CHINA Information Sciences, etc. He was a PI of 20 projects in the last five years, including the General Program of National Natural Science Foundation of China, and the Project for Jiangsu Natural Science Foundation of China, etc. He was awarded two Second Prize in China’s State Natural Science Award (ranking second), one First Prize in Natural Science Award of Ministry of Education (ranking second), two Second Prize in National Defense Science and Technology Progress (ranking first), and applied over 20 invention patents. He has published one English monograph and one Chinese monograph. He was published over 100 academic papers, more than 90 papers were published or accepted by international journals among these papers.
Title: Model Reference Resilient Control for Helicopter with Time-varying Disturbance
Abstract: In this talk, the problem of model reference resilient control is investigated for the helicopter system with time-varying disturbance and unmeasurable states. Firstly, a state observer and a disturbance observer are developed to estimate the unmeasurable states and the time-varying disturbance. Then, combining the methods of model reference control and disturbance-observer-based-control (DOBC), the state feedback robust resilient control scheme and the dynamic output feedback robust resilient control method are proposed, respectively. Under the developed two robust resilient control schemes, the sufficient conditions are obtained to guarantee that the helicopter system asymptotically tracks the reference model with performance. Finally, simulation results are presented to show the effectiveness of the model reference resilient control method.
Jun Fu, Professor, Northeastern University, China
Biography: Jun Fu is a full professor of state key lab of industrial process. He is deputy dean of the Institute of Artificial Intelligence, Northeastern University, China. He is a winner of China National Funds for Distinguished Young Scientists (NSFC).He won the 2018 Young Scientist Award in Science from MOE, China. He is associate editors of IEEE Trans. on Neural Networks and Learning Systems, IEEE Trans. on SMC: Systems, IFAC Control Engineering Practice, Journal of Industrial and Management Optimization. His main research interests include dynamic optimization, switching control, tracking control of robotic systems, and industrial artificial intelligence. He is a senior member of IEEE.
Title: Control and optimization of nonlinear dynamic systems
Abstract: This talk first presents a novel dynamic optimization algorithm based on the technique of the restriction of the right-hand side, which can guarantee that the path constraint is rigorously satisfied over the entire continuous time horizon within finite iterations; then introduces some novel methods in switching control and constructive control in nonlinear dynamic systems with their applications to the robotic systems.
Lianqing Liu, Professor, Shenyang Institute of Automation, Chinese Academy of Science, China
Biography: Lianqing Liu received his Ph.D. degree in Pattern Recognition and Intelligent System from university of Chinese Academy of Sciences, China in 2008, and B.S. degree in Industry Automation from Zhengzhou University, China in 2002. He started his career in 2006 at Shenyang Institute of Automation, Chinese Academy of Sciences, and holds the position of Assistant Professor (2006-2008), Associate Professor (2009-2010) and Professor (2011 to now) respectively. Currently his research interests include Nanorobotics, Intelligent control, and Biosensors. He has published over 100 peer reviewed international journal papers and led more than 20 funded research projects as Principal Investigator. 17 papers were selected as cover story published in “Small”, “Lab on a Chip” “Soft Matter”, “Applied Physics Letters” et al. He received the Best Student paper Award in 2015 International Conference on Manipulation, Manufacture and Measurement on the Nanoscale, Best Conference Paper in 2016 IEEE International Conference on Nano/Molecular Medicine and Engineering, and T. J. Tarn Best Paper in Robotics in 2017 IEEE international Conference on Robotics and Biomimetics.He was awarded the Early Government/Industrial Career Award by the IEEE Robotics and Automation Society in 2011, serves as a member of long range planning committee of RAS since 2017, and has been elected as the vice president of IEEE Robotics and Automation Society for the term of 2018-2019.
Title: Modeling, Fabrication and Control of Living Cell based modular Micro Robot
Abstract: Micro-robots have a great application prospect in the biomedical field due to the feature of small size. To solve the issues of energy supply and bio-compatibility of micro-robots, the bio-syncretic micro-robots actuated by living cells have been studied widely. However, the fabrication, assembling and control of the bio-syncretic micro-robots are the main challenges for the development of the bio-syncretic micro-robots. In this talk, manufacture and control ofthe living cells based modular micro robots will be discussed. Firstly, a robotic micro-manipulation system will be introduced to implement the high-throughput fabrication of the biological modules of micro robots, and to execute the on-line flexible assembling of the bio-syncretic robots by the fabricated living cells based modules. Then, an approach based on circularly distributed multiple electrodes (CE) will be induced to improve the differentiation of myoblast cells and characterize the electro-responsive beating behavior of living myotubes for the development of bio-syncretic micro robots.Moreover, a biomimetic bio-syncretic crawler actuated by living myotubes was demonstrated to move under the control of the CE.This talk will not only be related to the micro-robots, but will be also informative for biological tissue engineering and drugs screening.
Hongyi Li, Professor, Guangdong University of Technology, China
Biography: Hongyi Li received the Ph.D. degree in intelligent control from the University of Portsmouth, Portsmouth, U.K., in 2012. He was an Associate Researcher with the Department of Mechanical Engineering, University of Hong Kong, and Hong Kong Polytechnic University, Hong Kong. He was a Visiting Principal Fellow with the Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia. His current research interests include intelligent control, cooperative control and their applications. He was a recipient of the 2016 Andrew P. Sage Best Transactions Paper Award from IEEE System, Man, Cybernetics Society and the Best Paper Award in Theory from ICCSS 2017, respectively. He has been in the editorial board of several international journals, including IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man and Cybernetics: Systems, IEEE Transactions on Cognitive and Developmental Systems, IEEE/CAA Journal of Automatica Sinica etc. He has been Guest Editors of IEEE Transactions on Cybernetics and IET Control Theory and Applications. He is a member of the IFAC Technical Committee on Computational Intelligence in Control.
Title: Cooperative Control for Unmanned Autonomous Intelligent Systems
Abstract: Unmanned autonomous intelligent systems are quite important applications of the artificial intelligence. Unmanned autonomous intelligent systems are closely related to the development of cooperative control for multi-agent systems. The research of cooperative control has received considerable attention due to extensive applications of multi-agent networks. In this talk, firstly, the background and current situation of cooperative control for multi-agent systems are reported. Then, some main results are presented to address the problem of adaptive event-triggered control for a class of multi-agent systems with time-varying disturbance and faults. Finally, some challenges in this area are introduced.