CKSRI Seminar Series 2024 “Lifting for Nonlinear Systems and Model Predictive Control "

Thank you to everyone who joined the CKSRI Seminar!
We are honoured to have invited Prof. Yutaka Yamamoto, Professor Emeritus of Kyoto University, as our distinguished speaker. 

ABSTRACT:
This seminar has invited Prof. Yutaka Yamamoto, Professor Emeritus of Kyoto University, to discuss Nonlinear Systems and Model Predictive Control.

It is well recognized that the lifting technique has played a crucial role in modernizing the theory of sampled-data control. Unfortunately, this superb idea does not easily carry over to the nonlinear systems due to the outputs depending nonlinealy both on inputs and states.

This talk intends to circumvent this difficulty by lifting even the state trajectories.  While this can induce some difficulties, it still helps us to formalize nonlinear sampled-data control systems while maintaining intersample behavior - same advantage enjoyed in linear systems. We will give fast-sample/fast-hold approximation formulas to take care of computational difficulties, and then apply it to model predictive control.  Simulation results show that the proposed method exhibits an advantage in controlling the intersample behavior over the normal model predictive control focused on sample-point behavior.

SHORT BIO:
Yutaka Yamamoto received his B.S. and M.S. degrees in engineering from Kyoto University, Kyoto, Japan in 1972 and 1974, respectively, and the M.S. and Ph.D. degree in mathematics from the University of Florida, in 1976 and 1978, respectively. From 1978 to 1987 he was with Department of Applied Mathematics and Physics, Kyoto University. In 1987 he joined the Department of Applied Systems Science as an Associate Professor, and became a professor in 1997. He had been a professor at the Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics of Kyoto University until 2015. He is now Professor Emeritus of Kyoto University. 

His research and teaching interests are in realization and robust control of distributed parameter systems, learning control systems, and sampled-data systems, its application to digital signal processing, with emphasis on sound and image processing. He received Sawaragi memorial paper award in 1985, outstanding paper award of SICE in 1987 and in 1997, the best author award of SICE in 1990 and in 2000, the George S. Axelby Outstanding Paper Award in 1996, and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology Prizes for Science of Technology in 2007. He received the IEEE Control Systems Society Distinguished Member Award in 2009, and the Transition to Practice Award of the Control Systems Society in 2012, as well as the ISCIE Best Industrial Paper Award in 2009. He received the Tateishi Prize of the Tateishi Science and Technology Foundation in 2015.