2021 7th International Symposium on Sensors, Mechatronics and Automation System
Assoc. Prof. Yiyang Chen

Assoc. Prof. Yiyang Chen


Assoc. Prof. Yiyang Chen (Link)

School Of Mechanical And Electrical Engineering, Soochow University, China

Speech Title: The Background Theory and Recent Progress of Iterative Learning Control

Abstract: Iterative learning control (ILC) outperforms traditional control methods in terms of production quality while performing repetitive industrial manufacturing tasks. ILC algorithms have robustness, convergence and stability on the theoretical level, and have reliability, effectiveness and superiority in practical applications comparing to other control methods. This control technique does not require a large computation load, and it is relatively easy to implement, which demonstrates its feasibility in industrial manufacturing. This talk will introduce the background theory and theortical structure of ILC in detail, and hence introduce the recent progress in this research field. This talk will use case studies on industrial applications to illustrate the possible plan on the combination of ILC theory and application. The novelty of this talk concentrates on the cooperation between the advantages of ILC and massive repetitive industrial manufacturing tasks, so that a targeted ILC algorithm can be developed to bring a competitive application perspect as well as significant economic effect.

Brief introduction

Yiyang Chen obtained his MEng degree in Imperial College London in 2013. Then, He registered a PhD position in University of Southampton in 2013, and obtained PhD degree in 2017. After that, He worked as a Research Fellow in Control Systems during 2017-2018 and a Research Fellow in Traffic Signal Control during 2018-2020 respectively in University of Southampton. He joined Soochow University in 2020 as an Associate Professor in School of Mechanical and Electrical Engineering. He has published nearly 20 research papers including first author papers in IEEE Transactions on Control Systems Technology,Knowledge-based Systems,Mechatronics,Control Engineering Practice, which are top journals in control engineering and artificial intelligence.