Control, detection and estimation
Abstract: The main objective of this presentation is to give a unified view of feedback control, fault detection and estimation issues under the aspects of information and optimization. This would be helpful to achieve integrated design and implementation of fault diagnosis and fault-tolerant control schemes, both in the model-based and data-driven fashion.
Steven X. Ding
Institute for automatic control and complex systems (AKS)
University of Duisburg-Essen, Germany
Steven Dingreceived Ph.D. degree in electrical engineering from the Gerhard-Mercator University of Duisburg, Germany. He was a R&D engineer at Rheinmetall GmbH in Germany and became a professor of control engineering at the University of Applied Science Lausitz in Senftenberg, and served as a vice president of this university during 1998 – 2000. Since 2001, he has been a chair professor of control engineering and the head of the Institute for Automatic Control and Complex Systems (AKS) at the University of Duisburg-Essen. His research interests are model-based and data-driven fault diagnosis, control and fault-tolerant systems as well as their applications in industry with a focus on automotive systems, chemical processes and renewable energy systems.
Fault Detection and Diagnosis for Closed-Loop Dynamic Systems
Abstract: The model based fault diagnosis technique for dynamic systems has been developed over 40 years, however, most of the results are obtained for open-loop systems, very few results are concerning closed-loop systems. In this talk, the essential difference between open-loop and closed-loop fault diagnosis is analysedfirst, then a design method is given for the classical UIO method and the robust observer method to make themstill effective for closed-loop systems.A FDD design method is also give for a class of nonlinear systems. Finally, simulation and experiment results are given to illustrate the effectiveness of the proposed approaches.
D. H. Zhou
Vice president, Shandong University of Science and Technology
D. H. Zhou received the B.Eng., M. Sci., and Ph.D. degrees in electrical engineering from Shanghai Jiaotong University, China, in 1985, 1988, and 1990, respectively. He was an Alexander von Humboldt research fellow with the university of Duisburg, Germany from 1995 to 1996, and a visiting scholar with Yale university, USA from 2001 to 2002. He joined Tsinghua university in 1996, and was promoted as full professor in 1997, he was the head of the department of automation, Tsinghua university, during 2008 and 2015. He is now the vice president, Shandong University of Science and Technology. He has authored and coauthored over 170 peer-reviewed international journal papers and 6 monographs in the areas of process identification, fault diagnosis, fault-tolerant control, reliability prediction, and optimal maintenance. Dr. Zhou is a member of the IFAC TC on SAFEPROCESS, a senior member of IEEE, an associate editor of the Journal of Process Control, the vice Chairman of Chinese Association of Automation (CAA)， theChairman of the national high education steering committee on automation, the TC Chair of the SAFEPROCESS committee , CAA. He was also the NOC Chair of the 6th IFAC Symposium on SAFEPROCESS 2006.
New Idea, Theory, Principle and Methods for System Identification
Abstract: Control science casts the glory of our age, and the computer chips with high integration are the masterpiece of automation science and technology. The brilliant achievements of control science across time and space -- the abilities of the computing and information processing of electronic equipments and electronic products completely have changed and are changing the way of life, information society, and are beautifying our life.
Behind it, we cannot help but ask: what is control science and what is the foundation of control science?
Control science is to change the trajectory of things, make it develop in the direction we expect, on the basis of recognizing things' motion laws and by applying specific and wonderful control laws. The equations that describe the motion laws of things are the mathematical models. The mathematical models are the basis of control science and play an important role in control science development, and are the foundation of all sciences. System identification is the theory and methods of studying and establishing the mathematical models of dynamical systems.
This topic is to introduce some new idea, theory, principle, concept and methods of system identification, which involve the auxiliary model identification idea, the multi-innovation identification theory, the hierarchical identification principle, the coupling identification concept and methods. These can be applied to linear-parameter systems, bilinear-parameter systems, multi-linear-parameter systems, bilinear systems, nonlinear systems and generate numerous and various identification methods.
School of Internet of Things Engineering,
Jiangnan University, Wuxi, China
Professor Feng Ding was born in Guangshui, Hubei Province, China. He received the B.Sc. degree from the Hubei University of Technology (Wuhan, China) in 1984, and the M. Sc. and Ph.D. degrees in automatic control both from the Department of Automation, Tsinghua University (Beijing, China) in 1991 and 1994, respectively. He has been a Professor in the School of Internet of Things Engineering, Jiangnan University (Wuxi, China) since 2004.
From 1984 to 1988, he was an Electrical Engineer at the Hubei Pharmaceutical Factory, Xiangfan, China. From 1994 to 2002, he was with the Department of Automation, Tsinghua University, Beijing, China. From 2002 to 2005, he was a Research Associate at the University of Alberta, Edmonton, Canada. He was a Visiting Professor in the Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada from May to December 2008 and a Research Associate in the Department of Aerospace Engineering, Ryerson University, Toronto, Canada, from January to October 2009.
He has published over 512 papers and over 256 SCI indexed papers on system identification and parameter estimation. Sum of Cited Times is more than 10000, and Sum of Cited Times without self-citations is more than 7000.
He has published the book Adaptive Control Systems (Tsinghua University Press, Beijing, 2002), and the book Modern Control Theory (Tsinghua University Press, Beijing, 2017). He is publishing The Academic Monograph Series on System Identification: The 1st book System Identification -- New Theory and Methods (Science Press, Beijing, 2013), The 3rd book System Identification -- Performances Analysis for Identification Methods (Science Press, Beijing, 2014), The 4th book System Identification -- Auxiliary Model Identification Idea and Methods (Science Press, Beijing, 2017), The 6th book System Identification -- Multi-Innovation Identification Theory and Methods (Science Press, Beijing, 2016).
His current research interests include system identification and adaptive control.
Modeling, Control and Energy Management of PEM Fuel Cell systems
Abstract: Proton Exchange Membrane Fuel Cells (PEMFC) are electrochemical devices that convert the chemical energy of hydrogen into electricity through an electrochemical reaction of an hydrogen-containing fuel with oxygen. The result of this reaction is electrical energy, heat (thermal energy) and water, and consequently PEMFC are clean energy generators . Control systems play an important role in PEMFC technology. In this talk, different aspects related with the role of control technology in PEMFC will be described:
lPEMF Care complex systems that have to be operated appropriately in order to achieve good efficiency and improve lifetime. Usually PEMFC are used as part of great erhybrid systems. During the talk the role of PEMFC in different applications (stationary and mobile) will be described. How control systems are used to coordinate all elements in hybrid systems will be explained, too.
lPEMFC physical principles are described by partial differential equations. All relevant variables are distributed. This makes modeling, sensing and controlling a hard problem. During the talk, most relevant problems in modeling, controller design, parameter estimation and state observation in PEMFC will be described.
Universitat Politècnica de Catalunya (UPC), Spain
Dr Ramon Costa-Castellóobtained the master degree in computer sciencein 1993 from Universitat Politècnica de Catalunya (UPC); in 2001 he obtainedthe PhD degree in computer science from the Advanced Automation and Roboticsprogram at UPC. Currently, he is an Associate Professor at the AutomaticControl department from UPC. His teaching activity is related with differentaspects in automatic control. His research is mainly focused on analysis anddevelopment of energy management (automotive and stationary applications) andthe development of digital control techniques. He is a member of CEA and memberof IFAC (EDCOM, TC 9.4 Committee, Automotive Control T.C. 7.1) He has publishedmore than 40 journal paper and more 80 conference papers.
AdaptiveParameter Estimation and Control via Parameter Error: A New Framework
Abstract: Adaptive parameter estimation and adaptive control have been well developed for uncertain systems to improve modeling and control performance. However, the well-known parameter estimation and adaptive control methods have been mainly designed based on the gradient algorithms (with appropriate modifications) with prediction error or controlerror. Hence, the parameter estimation convergence and the online verificationof the required persistent excitation (PE) condition are not trivial in thisframework. In this talk, we will introduce a novel robust, fast adaptiveparameter estimation framework, where the parameter estimation error betweenthe unknown parameters and their estimates are explicitly obtained and then useto drive several online adaptation algorithms. This new adaptation even allowsto achieve finite-time parameter estimation. Moreover, we will introduce anintuitive and numerically feasible approach to online verify the PE condition.Finally, several practical application of this new adaptation to in-carparameters, adaptive control design and approximate dynamic programing forrobotics and will be presented.
Faculty of Electrical & Mechanical Engineering
Kunming University of Science & Technology, China
Prof. Jing Na is currently a Professor with the Faculty of Electrical & Mechanical Engineering at Kunming University of Science & Technology. He received the B.S. and Ph.D. degrees from Beijing Institute of Technology, China, in 2004 and 2010, respectively. He was a Marie Curie Fellow at the University of Bristol, UK (2015-2017), and a Monaco/ITER Postdoctoral Fellow with the ITER Organization, France (2011-2012). Since 2010,he has been with the Faculty of Mechanical and Electrical Engineering, Kunming University of Science & Technology, China, where he was promoted to be a full Professor in 2013. He has hold also visiting positions with the Universitat Politecnica de Catalunya, Spain (2008), and with the University of Bristol, UK (2009). Dr Na has been awarded the Best Application Paper Award of the 3rd IFAC International Conference on Intelligent Control and Automation Science (IFAC ICONS 2013), and the highly competitive EU Marie CurieIntra-European Fellowship. Dr Na has been Associated Editor for several journals (e.g. International Journal of Modelling, Identification and Control), and Program Committee Chair of The 9th International Conference on Modelling, Identification and Control (ICMIC 2017). He has organized and co-organized a few special issues and sessions on several prestigious journals and conferences (e.g. Complexity, IEEE CDC, UKACC, CCC) and served as an IPC member of several international conferences (e.g., IEEE CASE, IEEE CIS&RAM, IFAC ICONS, etc).His major research interests include adaptive parameter estimation, intelligent control, nonlinear control and applications. He has published more than 100peer reviewed journal and conference papers on these topics.