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Data driven discovery of cyber physical systems.

Accepted version
Peer-reviewed

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Authors

Tang, Xiuchuan 
Zhou, Wei 
Li, Xiuting 

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

4605 Data Management and Data Science, 46 Information and Computing Sciences, 40 Engineering

Journal Title

Nat Commun

Conference Name

Journal ISSN

2041-1723
2041-1723

Volume Title

10

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved