Name
Abstract | ||
|---|---|---|
Cyber-physical systems (CPSs) embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, intelligent manufacture and medical monitoring. CPSs have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical components and cyber components and the interaction between them. This study proposes a general framework for reverse engineering CPSs directly from data. The method involves the identification of physical systems as well as the inference of transition logic. It has been applied successfully to a number of real-world examples ranging from mechanical and electrical systems to medical applications. The novel framework seeks to enable researchers to make predictions concerning the trajectory of CPSs based on the discovered model. Such information has been proven essential for the assessment of the performance of CPS, the design of failure-proof CPS and the creation of design guidelines for new CPSs. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Systems and Control | Mathematical optimization,Data-driven,Smart grid,Physical system,Inference,Reverse engineering,Software,Cyber-physical system,Artificial intelligence,Robotics,Mathematics,Distributed computing |
DocType | Volume | Citations |
Journal | abs/1810.00697 | 0 |
PageRank | References | Authors |
0.34 | 3 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ye Yuan | 1 | 438 | 61.04 |
| Xiuchuan Tang | 2 | 0 | 0.34 |
| Wei Pan | 3 | 44 | 5.22 |
| Xiuting Li | 4 | 0 | 0.68 |
| Wei Zhou | 5 | 112 | 27.01 |
| Hai-Tao Zhang | 6 | 83 | 14.27 |
| Han Ding | 7 | 499 | 78.16 |
| Jorge Goncalves | 8 | 60 | 5.79 |