Controller dependability analysis by probabilistic model checking

Kwiatkowska, M., Norman, G. and Parker, D. (2007) Controller dependability analysis by probabilistic model checking. Control Engineering Practice, 15(11), pp. 1427-1434. (doi:10.1016/j.conengprac.2006.07.003)

Full text not currently available from Enlighten.

Abstract

This paper demonstrates how probabilistic model checking, a formal verification method for the analysis of systems which exhibit stochastic behaviour, can be applied to the study of dependability properties of software-based control systems. By using existing formalisms and tool support from this area, it is possible to construct large and complex Markov models from an intuitive high-level description and to take advantage of the efficient implementation techniques which have been developed for these tools. This paper provides an overview of probabilistic model checking and of the tool PRISM which supports these techniques. It illustrates the applicability of the approach through the use of a case study and demonstrates that a wide range of useful dependability properties can be analysed in this way.

Item Type:Articles
Additional Information:Special Issue on Manufacturing Plant Control: Challenges and Issues - INCOM 2004, 11th IFAC INCOM'04 Symposium on Information Control Problems in Manufacturing
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Norman, Dr Gethin
Authors: Kwiatkowska, M., Norman, G., and Parker, D.
Subjects:T Technology > T Technology (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Control Engineering Practice
Publisher:Elsevier Science B.V.
ISSN:0967-0661
Published Online:12 September 2006

University Staff: Request a correction | Enlighten Editors: Update this record