Scalable methods of discrete plant model generation for closed-loop model checking

Igor Buzhinsky; Antti Pakonen; Valeriy Vyatkin

doi:10.1109/IECON.2017.8216949

Scalable methods of discrete plant model generation for closed-loop model checking

Igor Buzhinsky, Antti Pakonen, Valeriy Vyatkin

VTT Technical Research Centre of Finland

Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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Abstract

To facilitate correctness and safety of mission-critical automation systems, formal methods should be applied in addition to simulation and testing. One of such formal methods is model checking, which is capable of verifying complex requirements for the system's model. If both the controller and the controlled plant are formally modeled, then the variant of this technique called closed-loop model checking can be applied. Recently, a technique of automatic plant model generation has been proposed which is applicable in this scenario. This paper continues the work in this direction by presenting two plant model construction approaches which are much more scalable with respect to the previous one, and puts this work into a more practical context. The approaches are evaluated on a case study from the nuclear automation domain.

Original language	English
Title of host publication	Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	5483-5488
Number of pages	6
ISBN (Electronic)	978-1-5386-1127-2
DOIs	https://doi.org/10.1109/IECON.2017.8216949
Publication status	Published - 15 Dec 2017
MoE publication type	A4 Article in a conference publication
Event	43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, China Duration: 29 Oct 2017 → 1 Nov 2017 Conference number: 43

Conference

Conference	43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Abbreviated title	IECON 2017
Country/Territory	China
City	Beijing
Period	29/10/17 → 1/11/17

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title = "Scalable methods of discrete plant model generation for closed-loop model checking",

abstract = "To facilitate correctness and safety of mission-critical automation systems, formal methods should be applied in addition to simulation and testing. One of such formal methods is model checking, which is capable of verifying complex requirements for the system's model. If both the controller and the controlled plant are formally modeled, then the variant of this technique called closed-loop model checking can be applied. Recently, a technique of automatic plant model generation has been proposed which is applicable in this scenario. This paper continues the work in this direction by presenting two plant model construction approaches which are much more scalable with respect to the previous one, and puts this work into a more practical context. The approaches are evaluated on a case study from the nuclear automation domain.",

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Buzhinsky, I, Pakonen, A & Vyatkin, V 2017, Scalable methods of discrete plant model generation for closed-loop model checking. in Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. IEEE Institute of Electrical and Electronic Engineers, pp. 5483-5488, 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017, Beijing, China, 29/10/17. https://doi.org/10.1109/IECON.2017.8216949

Scalable methods of discrete plant model generation for closed-loop model checking. / Buzhinsky, Igor; Pakonen, Antti; Vyatkin, Valeriy.

Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. IEEE Institute of Electrical and Electronic Engineers, 2017. p. 5483-5488.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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N2 - To facilitate correctness and safety of mission-critical automation systems, formal methods should be applied in addition to simulation and testing. One of such formal methods is model checking, which is capable of verifying complex requirements for the system's model. If both the controller and the controlled plant are formally modeled, then the variant of this technique called closed-loop model checking can be applied. Recently, a technique of automatic plant model generation has been proposed which is applicable in this scenario. This paper continues the work in this direction by presenting two plant model construction approaches which are much more scalable with respect to the previous one, and puts this work into a more practical context. The approaches are evaluated on a case study from the nuclear automation domain.

AB - To facilitate correctness and safety of mission-critical automation systems, formal methods should be applied in addition to simulation and testing. One of such formal methods is model checking, which is capable of verifying complex requirements for the system's model. If both the controller and the controlled plant are formally modeled, then the variant of this technique called closed-loop model checking can be applied. Recently, a technique of automatic plant model generation has been proposed which is applicable in this scenario. This paper continues the work in this direction by presenting two plant model construction approaches which are much more scalable with respect to the previous one, and puts this work into a more practical context. The approaches are evaluated on a case study from the nuclear automation domain.

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BT - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017

Y2 - 29 October 2017 through 1 November 2017

ER -

Scalable methods of discrete plant model generation for closed-loop model checking

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