[en] Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber- physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Yuan, Ye; Huazhong University of Science and Technology > Key Laboratory of Image Processing and Intelligent Control
Tang, Xiuchuan; Huazhong University of Science and Technology > School of Mechanical Science and Engineering
Zhou, Wei; Huazhong University of Science and Technology > Key Laboratory of Image Processing and Intelligent Control
Pan, Wei; Delft University of Technology > Department of Cognitive Robotics
Li, Xiuting; Huazhong University of Science and Technology > Key Laboratory of Image Processing and Intelligent Control
Zhang, Hai-Tao; Huazhong University of Science and Technology > Key Laboratory of Image Processing and Intelligent Control
Ding, Han; Huazhong University of Science and Technology > School of Mechanical Science and Engineering
GONCALVES, Jorge ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
External co-authors :
yes
Language :
English
Title :
Data driven discovery of cyber physical systems
Publication date :
25 October 2019
Journal title :
Nature Communications
eISSN :
2041-1723
Publisher :
Nature Publishing Group, London, United Kingdom
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Systems Biomedicine
FnR Project :
FNR10907093 - Critical Transitions In Complex Systems: From Theory To Applications, 2015 (01/11/2016-30/04/2023) - Jorge Gonçalves