Data driven discovery of cyber physical systems

被引:171
作者
Yuan, Ye [1 ,2 ]
Tang, Xiuchuan [3 ]
Zhou, Wei [1 ]
Pan, Wei [4 ]
Li, Xiuting [1 ]
Zhang, Hai-Tao [1 ,2 ]
Ding, Han [2 ,3 ]
Goncalves, Jorge [1 ,5 ,6 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Hubei, Peoples R China
[2] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan 430074, Hubei, Peoples R China
[4] Delft Univ Technol, Dept Cognit Robot, Delft, Netherlands
[5] Univ Cambridge, Dept Plant Sci, Cambridge CB2 3EA, England
[6] Univ Luxembourg, Luxembourg Ctr Syst Biomed, 6 Ave Swing, L-4367 Luxembourg, Luxembourg
基金
中国国家自然科学基金;
关键词
PIECEWISE AFFINE SYSTEMS; HYBRID SYSTEMS; IDENTIFICATION; RECONSTRUCTION; REGRESSION; MODELS;
D O I
10.1038/s41467-019-12490-1
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 cyberphysical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance.
引用
收藏
页数:9
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