A case study on knowledge driven code generation for software-defined industrial cyber-physical systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Research units

  • University of California at Berkeley
  • Shanghai Jiao Tong University
  • Jiangmen Goobotics Research Institute
  • Luleå University of Technology


Industrial Cyber-Physical Systems (iCPS) enable coordination between various subsystems and devices based on real-time feedback data from sensors. iCPS must react rapidly to new requirements and adjust itself to fulfill new functionalities in no time. On the software side, control programs of iCPS need to be reconfigured dynamically. An efficient way for massive reconfiguration is automatic code generation. In this paper, a knowledge-driven code generation method is experimented for software-defined iCPS. Based on sensor values, actuators are controlled by the reasoning process with support of ontological knowledge base. The results demonstrate that iCPS could be driven by rules completely without programming control software.


Original languageEnglish
Title of host publicationProceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
Publication statusPublished - 26 Dec 2018
MoE publication typeA4 Article in a conference publication
EventAnnual Conference of the IEEE Industrial Electronics Society - Washington, United States
Duration: 21 Oct 201823 Oct 2018
Conference number: 44

Publication series

NameProceedings of the Annual Conference of the IEEE Industrial Electronics Society
ISSN (Print)1553-572X


ConferenceAnnual Conference of the IEEE Industrial Electronics Society
Abbreviated titleIECON
CountryUnited States

    Research areas

  • Cod generation, Industrial cyber-physical systems, Ontology reasoning, Requirement engineering, Software-defined systems, SQWRL, SWRL

ID: 32397360