Title
Active Learning Of Formal Plant Models For Cyber-Physical Systems
Abstract
As the world becomes more and more automated, the degree of cyber-physical systems involvement cannot be overestimated. A large part of them are safety-critical, thus, it is especially important to ensure their correctness before start of operation or reconfiguration. For this purpose the model checking approach should be used since it allows rigorously proving system correctness by checking all possible states. To ensure the compliance of controller-plant properties with system requirements, the closed-loop verification approach should be chosen, which requires not only a formal model of the controller, but also a formal model of the plant. In this paper we propose an approach for constructing formal models of context-free deterministic plants automatically using active learning algorithms. The case study shows its successful application to plant model generation for the elevator cyber-physical system.
Year
Venue
Field
2018
2018 IEEE 16TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)
Control theory,Model checking,Active learning,Systems engineering,Software engineering,Correctness,Context model,Cyber-physical system,Engineering,System requirements,Control reconfiguration
DocType
ISSN
Citations 
Conference
1935-4576
0
PageRank 
References 
Authors
0.34
0
7