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Domain-driven Probabilistic Analysis of Programmable Logic Controllers

Hehua Zhang 1 Yu Jiang 1 Hung William N.N. 1 Xiaoyu Song 1 Ming Gu 1 
1 FORMES - Formal Methods for Embedded Systems
LIAMA - Laboratoire Franco-Chinois d'Informatique, d'Automatique et de Mathématiques Appliquées, Inria Paris-Rocquencourt
Abstract : Programmable Logic Controllers are widely used in industry. Reliable PLCs are vital to many critical applications. This paper presents a novel symbolic approach for analysis of PLC systems. The main components of the approach consists of: (1) calculating the uncertainty characterization of the PLC systems, (2) abstracting the PLC system as a Hidden Markov Model, (3) solving the Hidden Markov Model using domain knowledge, (4) integrating the solved Hidden Markov Model and the uncertainty characterization to form an integrated (regular) Markov Model, and (5) harnessing probabilistic model checking to analyze properties on the resultant Markov Model. The framework provides expected performance measures of the PLC systems by automated analytical means without expensive simulations. Case studies on an industrial automated system are performed to demonstrate the effectiveness of our approach.
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Submitted on : Wednesday, August 10, 2011 - 5:59:10 AM
Last modification on : Thursday, February 3, 2022 - 11:16:25 AM
Long-term archiving on: : Friday, November 11, 2011 - 2:20:20 AM


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  • HAL Id : inria-00612414, version 1



Hehua Zhang, Yu Jiang, Hung William N.N., Xiaoyu Song, Ming Gu. Domain-driven Probabilistic Analysis of Programmable Logic Controllers. 13th International Conference on Formal Engineering Methods(ICFEM 2011), Oct 2011, Durham, United Kingdom. ⟨inria-00612414⟩



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