ICCRE 2019 Keynote & Plenary Speakers
Prof. Makoto Iwasaki, IEEE Fellow
Nagoya Institute of Technology, Japan
Biography: Makoto Iwasaki received the B.S., M.S., and Dr. Eng. degrees in electrical and computer engineering from Nagoya Institute of Technology, Nagoya, Japan, in 1986, 1988, and 1991, respectively. Since 1991, he has been with the Department of Computer Science and Engineering, Nagoya Institute of Technology, where he is currently a Professor at the Department of Electrical and Mechanical Engineering.
As professional contributions of the IEEE, he has been an AdCom member of the Industrial Electronics Society in term of 2010 to 2019, a Technical Editor for IEEE/ASME Transactions on Mechatronics from 2010 to 2014, an Associate Editor for IEEE Transactions on Industrial Electronics since 2014, a Management Committee member of IEEE/ASME Transactions on Mechatronics (Secretary in 2016 and Treasurer in 2017), a Co-Editors-in-Chief for IEEE Transactions on Industrial Electronics since 2016, a Vice President for Planning and Development in term of 2018 to 2019, respectively. He is IEEE fellow class 2015 for "contributions to fast and precise positioning in motion controller design". He has received the Best Paper Award of Trans of IEE Japan in 2013, the Best Paper Award of Fanuc FA Robot Foundation in 2011, the Technical Development Award of IEE Japan in 2017, The 3rd Nagamori Awards in 2017, The 50th Ichimura Prize in Industry for Excellent Achievement in 2018, and the Technology Award of the Japan Society for Precision Engineering in 2018, respectively.
His current research interests are the applications of control theories to linear/nonlinear modeling and precision positioning, through various collaborative research activities with industries.
Title of Speech: Fast and Precision Motion Control for Industrial Positioning Devices
Abstract: Fast-response and high-precision motion control is one of indispensable techniques in a wide variety of high performance mechatronic systems including micro and/or nano scale motion, such as data storage devices, machine tools, manufacturing tools for electronics components, and industrial robots, from the standpoints of high productivity, high quality of products, and total cost reduction. In those applications, the required specifications in the motion performance, e.g. response/settling time, trajectory/settling accuracy, etc., should be sufficiently achieved. In addition, the robustness against disturbances and/or uncertainties, the mechanical vibration suppression, and the adaptation capability against variations in mechanisms should be essential properties to be provided in the performance.
The keynote speech presents the fast and precision motion control techniques, where a 2-degrees-of-freedom (2-DoF) control framework is especially handled as one of practical and/or promising approaches to improve the motion performance. Actual issues and relevant solutions for each component in the 2-DoF control structure are clarified, and then, one of examples, a 2-DoF controller design for robust vibration suppression positioning, is presented as an application to industrial high precision positioning devices. In this speech, especially, a command shaping technique with robust performance is discussing for typical industrial manufactural machines, considering mechanical vibration suppression, input saturation, and plant perturbations.
Prof. Mou Chen | 陈谋教授
Nanjing University of Aeronautics and Astronautics, China | 南京航空航天大学
Biography: Mou Chen is now a professor and vice Dean of the College of Automation Engineering, 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 received the BSc degree and the PhD degree in Nanjing University of Aeronautics and Astronautics. 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 board 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 10 invention patents. He has published one English monograph and one Chinese monograph. He was published over 100 academic papers, more than 80 papers were published or accepted by international journals among these papers.
Title of Speech: 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.
Prof. Chih-Shing (Stan) Wei
The Cooper Union for the Advancement of Science and Art, USA
Biography: Dr. Chih-Shing (Stan) Wei is presently the George Clark Professor of Mechanical Engineering at The Cooper Union for the Advancement of Science and Art, in New York. He received his Ph.D. in 1982 from Georgia Tech in Atlanta. That same year he started his academic career, first at the Polytechnic Institute of New York (now NYU Tandon School of Engineering). At Polytechnic, he helped establish a CAD/CAM program at its Department of Mechanical Engineering. He also consulted for General Motors and Ford in a number of collaborative R&D projects aimed at advancing the field of computer-based modeling of metal casting processes. Since joining Cooper Union in 1988, he has established Cooper’s Manufacturing and Industrial Robotics Lab, and taught courses in manufacturing engineering, cloud-based design and manufacturing, and industrial robotics. More recently, he has expanded his research interests into biomedical engineering and use of haptics in healthcare applications, and published reports/papers, collaborated with Dr. Peter Walker of NYU School of Medicine, in the areas of arthroplasty instrumentation and replacement knee component design. Dr. Wei has published one book, on CAD, and more than 50 technical papers, and has received six U.S. patents.
Title of Speech: Cloud Robotics
Abstract: A Cloud Robot is known as a robotic system that relies on data or code from a cloud network to support its operation. This scenario enables the robot to deliver and perform functions that are beyond the capacity of its locally integrated sensors, actuators, and computer. This presentation will examine the current state of this art and explore the leading trends in the continuing development of this technology.
Prof. Susumu Hara
Nagoya University, Japan
Biography: Susumu Hara received his BS, MS, and PhD degrees from Keio University, Tokyo, Japan in 1992, 1994, and 1996, respectively, all in engineering. From 1995 to 2000, he was a Research Fellow with the Japan Society for the Promotion of Science. From 1996 to 2000, he was a Visiting Researcher with the Faculty of Science and Technology, Keio University. From 1998 to 1999, he was a Visiting Scholar with the Department of Mechanical Engineering, University of California, Berkeley. In 2000, he joined the faculty of Toyota Technological Institute, Nagoya, Japan. In 2008, he joined the faculty of Nagoya University, Nagoya, Japan, where he is currently a Professor in the Department of Aerospace Engineering, Graduate School of Engineering. His current research interests include motion and vibration control of mechanical structures and spacecraft, nonstationary control methods, and control problems of man machine systems. He is a member of the JSME, SICE, RSJ, IEEJ, JSPE, IEEE, AIAA, and JSASS.
Title of Speech: Experience-Based Lecture of Vibration and Control Engineering Using Dual Scale Experiments
Abstract: This plenary talk presents an experience-based lecture style for vibration and control engineering in Nagoya University. In the proposed style, experiments of the free vibration using a seismic building with vibration isolation layer and advanced vibration control using an effective small device are provided in combination. In the first trial of this lecture style in 2015, two hundreds of second-year students felt the free vibration of the five-story building with a weight of 5,600 ton inside the building and witnessed the mechanism of the isolation layer. To follow the demonstration experimentally, we have built a small experimental system. The device is composed of a vibration component (flexible structure) corresponding to the building and a cart with a handle corresponding to the ground. They are connected via a linear actuator corresponding to the isolation layer. Students oscillate the cart and observe the motion of the vibration component. In addition, the system has virtual reality cameras to attract students' interest and reduce the size gap influence of the real building and the small experimental system. The second lecture was conducted in 2017. A questionnaire showed that 100% of students valued the lecture style as useful. Since 90% of students valued that providing largescale demonstration lecture and the second lecture in combination as useful, the proposed style achieved a certain result.
Prof. Juntao Fei | 费俊涛教授
Hohai University, China | 河海大学
Biography: Professor Juntao Fei received his B.S. degree from the Hefei University of Technology in 1991, M.S. degree from University of Science and Technology of China in 1998, M.S and Ph.D. degree from the University of Akron, USA in 2003 and 2007 respectively. He was a visiting scholar at University of Virginia, USA from 2002 to 2003, North Carolina State University, USA from 2003 to 2004 respectively. He served as an assistant professor at the University of Louisiana, USA from 2007 to 2009. Since May 2009, He has been a Professor at the College of IoT Engineering, Hohai University , Director of Institute of Electrical and Control Engineering. His research interests include adaptive control, intelligent control, sliding mode control, power electronics and control, mechatronics and robotics, smart material and structure. He is a Senior Member of IEEE. He has served as an associate editor for Transactions of the Institute of Measurement and Control, reviewers for numerous international journals, program committee members and chairs for numerous international conferences. He has published more than 200 journal and conference papers and 5 books and led more than 20 funded research projects to completion as Principal Investigator. He authorized 40 invention patents. He is an awardee of the Recruitment Program of Global Experts (China). His biography has been included in Who’s Who in the World, Who’s Who in Science and Engineering, Who’s Who in America.
Title of Speech: Adaptive Double Hidden Layer Neural Network Sliding Mode Control of Active Power Filter
Abstract: In this paper, a full-regulated recurrent neural structure which has double hidden layer neural network (DHLRNN) is designed. Then, an adaptive global sliding mode controller based on the double hidden layer recurrent neural network is proposed to improve the performance of harmonic current compensation and system robustness of Active Power Filter (APF). Six parameters of the double hidden layer recurrent neural designed in this paper can adaptively stabilize to their best values according to different inputs. Compared with the gener RBF neural network with single hidden layer, the double hidden layer neural network can improve the accuracy and generalization ability of the network, reduce the number of network weights and accelerate the network training speed owing to the strong fitting and presentation ability of two-layer activation functions. The feedback neural network plays the significant role in possessing associative memory and rapid system convergence. Simulation and experiment demonstrated that the satisfactory performance of proposed controller under both dynamic and steady state operations, including robustness, fast response, and small overshoot for harmonic suppression.