Data driven discovery of cyber physical systems

• Published in: Nature communications Vol. 10; no. 1; pp. 4894 - 9
• Main Authors: Yuan, Ye, Tang, Xiuchuan, Zhou, Wei, Pan, Wei, Li, Xiuting, Zhang, Hai-Tao, Ding, Han, Goncalves, Jorge
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 25.10.2019; Nature Publishing Group UK; Nature Portfolio
• Subjects: Access control; Automation; Cyber-physical systems; Debugging; Embedded systems; Industrial robots; Intelligent manufacturing systems; Manufacturing engineering; Redesign; Robotics; Smart grid
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-019-12490-1

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.