学术动态

波兰绿山大学Krzysztof Galkowski教授学术报告会

发布人:安剑奇发表时间:2020-03-17点击:

http://au.cug.edu.cn/__local/8/A6/D9/14FBA41964D3635C8F76272A657_57D2903B_F7A.jpg

报告形式:腾讯会议

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:319日(星期四)15:00 – 16:30

ID642     064 649

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:323日(星期一)15:00 – 16:30

ID652     398 429

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:324日(星期二)15:00 – 16:30

ID390     518 292

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.