Domain-Driven Probabilistic Analysis of Programmable Logic Controllers View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2011

AUTHORS

Hehua Zhang , Yu Jiang , William N. N. Hung , Xiaoyu Song , Ming Gu

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. More... »

PAGES

115-130

References to SciGraph publications

  • 2006. PRISM: A Tool for Automatic Verification of Probabilistic Systems in TOOLS AND ALGORITHMS FOR THE CONSTRUCTION AND ANALYSIS OF SYSTEMS
  • 2004. Verification of PLC Programs Given as Sequential Function Charts in INTEGRATION OF SOFTWARE SPECIFICATION TECHNIQUES FOR APPLICATIONS IN ENGINEERING
  • Book

    TITLE

    Formal Methods and Software Engineering

    ISBN

    978-3-642-24558-9
    978-3-642-24559-6

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-24559-6_10

    DOI

    http://dx.doi.org/10.1007/978-3-642-24559-6_10

    DIMENSIONS

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