报告形式：腾讯会议
报 告 人：Krzysztof Galkowski，波兰绿山大学（University of Zielona Gora）教授
报告主题：Machine Learning and Iterative Learning Control
（一）
报告时间：3月17日（星期五）16:05 – 17:35
会 议 ID：392-664-076
报告题目：Elements of multidimensional systems and repetive processes theory and applications
主要内容：Multi-dimensional systems dynamics and signals are dependent on more than one indeterminate. These are usually time and spatial variables. However, in various applications, as e.g. later discussed Iterative Learning Control, they can be the number of the system action execution (trial). Hence, they are governed by differential or difference (discrete case) or mixed equations in many indeterminates.
In this lecture the basics of multidimensional signals and systems and also repetive processes treated from this point of view will be presented. Some basic models and applications will be shown and discussed.
（二）
报告时间：3月22日（星期三）16:05 – 17:35
会 议 ID：722-843-001
报告题目：Repetitive processes theory and applications – continuation
主要内容：Repetitive processes are the particular case of multidimensional systems where except time, the number of repetition serves as an additional system indeterminate. This represents the situation where the process dynamics dep[ends on the previous (in time) system states but also on its previous execution.
In this lecture, properties and control of various repetitive process models and their applications will be discussed, from the standpoint of multidimensional systems.
（三）
报告时间：3月24日（星期五）16:05 – 17:35
会 议 ID：256-124-582
报告题目：Iterative Learning Control (ILC)
主要内容：Iterative learning control can be applied to systems that execute the same finite duration task over and over again. The distinguishing feature is the use of information from previous executions to construct the input to the next one in the sequence, including time domain information that would be non-causal in standard control systems. Many algorithms or laws have been developed for an ever increasing range of applications.
Iterative learning control, or ILC for short, has been developed for such systems where the distinguishing feature is the use of information from previous trials to update the control signal applied on the next one. In particular, once the system has completed each trial, the complete information generated is available for use in computing the control signal to be applied on the next trial with the aim of sequentially improving performance from trial-to-trial. A major application area for both these approaches is industrial robotics, but many others have also arisen in the engineering domain as e.g. motor control and many others.
Based on the previous lectures, various schemes of Iterative Learning Control (ILC), together with particular solutions and applications will be presented. In particular, ILC has been extended to encounter guaranteed cost control methods, feedforward techniques and the use of disturbance observer. The results have been highlighted by experimental testing of PMSM Position Control system.
报告人简介：Dr. Krzysztof Galkowski received his Ph.D. degrees from Technical University of Wroclaw in 1977. After a twenty-year stint at the University of Wroclaw, he joined the University of Zielona Gora in 1996, where he is currently a Professor of Institute of Control and Computation Engineering. Professor Galkowski is an inventor of the effective and still being generalised by other researchers, method of the construction of a state-space realization for the multidimensional (n-variate) transfer function matrices, called Elementary Operation Algorithm. His research interests include multidimensional (nD) systems and repetitive processes-theory and applications, Iterative Learning Control and related numerical methods. He is an author/editor of four monographs/books and over 100 papers in the leading peer reviewed journals and over 180 in the proceedings of international conferences. He has given numerous invited plenary talks for international conferences and in many universities (Europe, USA, Canada, China, Australia, India). He, as well, has prepared numerous special issues for leading journals as IJC, MDSSP and others. He has a strong international co-operation with the Universities of Southampton, UK; the universities of Wuppertal, Rostock and Erlangen-Nurnberg, Germany; University of Hong Kong; University of Poitiers, France; University of Thessaloniki, Greece; East China University of Science and Technology, Shanghai; Harbin Institute of Technology, Harbin; Central South University, Changsha; China University of Geosciences, Wuhan, and many others.
Dr. Krzysztof Galkowski is an associate editor for IET Control Theory and Applications, and a member of editorial board of International Journal of Multidimensional Systems and Signal Processing and International Journal of Control. He served as a member of IPC for several international conferences and co-organised a series of international workshops.
