CPN Modeling and Dangerous State Identification of Aircraft Engine Control Software
Abstract— Aircraft engine control software is the core control software of the aircraft, and its safety is very important. How to construct the model of the software and effectively identify the dangerous state is also a difficult point to study the safety of the aircraft engine control software. This paper uses the colored Petri net (CPN) to model the aircraft engine control software, and then use the improved genetic algorithm to identify the dangerous state of the software. Finally, the method of this paper is applied to a real aircraft engine control software to implement CPN modeling and dangerous state identification. The results show that the method proposed in this paper can identify the dangerous state in the software. And through the improvement of the genetic algorithm, the execution efficiency of the recognition algorithm is improved.
Index Terms— aircraft engine control software, colored petri nets, genetic algorithm.
Shunyao Kang, Chenxin Wang
College of Information Science and Technology, Beijing University of Chemical Technology, CHINA
Cite: Shunyao Kang, Chenxin Wang, "CPN Modeling and Dangerous State Identification of Aircraft Engine Control Software," Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering, pp. 7-13, Bangkok, 28-30 June, 2018.