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Data driven discovery of cyber physical systems

Published version
Peer-reviewed

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Authors

Tang, Xiuchuan 
Zhou, Wei 
Li, Xiuting 

Abstract

Abstract: 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.

Description

Keywords

Article, /639/705/1042, /639/766/530/2803, /129, /141, /139, article

Journal Title

Nature Communications

Conference Name

Journal ISSN

2041-1723

Volume Title

10

Publisher

Nature Publishing Group UK