Bidirectional fragmentation approach on the stability analysis of sampled-data linear systems

Abstract

In this paper, a novel stability analysis method for continuous-time linear systems with aperiodic sampling is presented by using a partitioned looped-functional approach. Based on the Lyapunov function with a new looped-functional, the stability condition is derived by using a bidirectional fragmentation of a sampling interval from $t_k$ to $t_{k+1}$, which is divided into two sides forward and backward directions based on time t. For the bidirectional regions, the new looped functional is constructed by taking into account relations between states defined at the fragmented time and the sampling time. The improvement using the proposed scheme is shown through the comparisons with existing methods.

Keywords:

• Sampled-data systems
• looped functional
• Lyapunov stability

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, S.M. Lee, upon reasonable request.

Additional information

Funding

This research was funded by Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean government (21ZD1130, Development of ICT Convergence Technology for Daegu-Gyeongbuk Regional Industry) and the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2019R1I1A3A01060151).

Notes on contributors

Wookyong Kwon

Wookyong Kwon received the B.S., M.S., and Ph.D. degrees from the Pohang University of Science and Technology (POSTECH), Pohang, South Korea, in 2011, 2012, and 2017, respectively. He was a Postdoctoral Researcher with the Department of Creative IT Engineering, POSTECH. He is currently a Researcher with the Electronics and Telecommunications Research Institute (ETRI), Daegu, South Korea. His research interests include control and automation, multiobjective control, robot manipulator, and deep neural networks.

JunMin Park

JunMin Park received the Ph.D. degree in electronics engineering from POSTECH, Pohang, South Korea, in 2019. He is currently a Assistant Professor at the Department of Electronics Engineering, Chungnam National University. His main research interests include control theory, networked control systems, fuzzy systems.

Sangmoon Lee

Sangmoon Lee received the M.S and Ph.D. degrees in electronics engineering from POSTECH, Pohang, South Korea, in 2001 and 2006, respectively. He is currently a Professor at the School of Electronic and Electrical Engineering, Kyungpook National University. His main research interests include cyber-physical systems control, networked control systems, fuzzy systems, model predictive control, reinforcement learning, and its industrial applications.