Control, detection and estimation
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.
teven X. Ding
Institute for automatic control and complex systems (AKS)
University of Duisburg-Essen, Germany
Prof. Steven Ding received 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.
Modeling, Control andEnergy Management of PEM Fuel Cell systems
ProtonExchange Membrane Fuel Cells (PEMFC) are electrochemical devices that convertthe chemical energy of hydrogen into electricity through an electrochemicalreaction of an hydrogen-containing fuel with oxygen. The result of thisreaction is electrical energy, heat (thermal energy) and water, and consequentlyPEMFC are clean energy generators . Control systems play an important role inPEMFC technology. In this talk, different aspects related with the role ofcontrol technology in PEMFC will be described:
lPEMFCare complex systems that have to be operated appropriately in order to achievegood efficiency and improve lifetime. Usually PEMFC are used as part of greaterhybrid systems. During the talk the role of PEMFC in different applications(stationary and mobile) will be described. How control systems are used tocoordinate all elements in hybrid systems will be explained, too.
lPEMFCphysical principles are described by partial differential equations. Allrelevant variables are distributed. This makes modeling, sensing andcontrolling a hard problem. During the talk, most relevant problems inmodeling, controller design, parameter estimation and state observation inPEMFC will be described.
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
Adaptive parameterestimation and adaptive control have been well developed for uncertain systemsto improve modeling and control performance. However, the well-known parameterestimation and adaptive control methods have been mainly designed based on the gradientalgorithms (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.
Prof. Jing Na is currently a Professor with theFaculty of Electrical & Mechanical Engineering at Kunming University ofScience & Technology. He received the B.S. and Ph.D. degrees from BeijingInstitute of Technology, China, in 2004 and 2010, respectively. He was a MarieCurie Fellow at the University of Bristol, UK (2015-2017), and a Monaco/ITERPostdoctoral Fellow with the ITER Organization, France (2011-2012). Since 2010,he has been with the Faculty of Mechanical and Electrical Engineering, KunmingUniversity of Science & Technology, China, where he was promoted to be afull Professor in 2013. He has hold also visiting positions with theUniversitat Politecnica de Catalunya, Spain (2008), and with the University ofBristol, UK (2009). Dr Na has been awarded the Best Application Paper Award ofthe 3rd IFAC International Conference on Intelligent Control and AutomationScience (IFAC ICONS 2013), and the highly competitive EU Marie CurieIntra-European Fellowship. Dr Na has been Associated Editor for severaljournals (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 afew special issues and sessions on several prestigious journals and conferences(e.g. Complexity, IEEE CDC, UKACC, CCC) and served as an IPC member of severalinternational conferences (e.g., IEEE CASE, IEEE CIS&RAM, IFAC ICONS, etc).His major research interests include adaptive parameter estimation, intelligentcontrol, nonlinear control and applications. He has published more than 100peer reviewed journal and conference papers on these topics.