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Adaptive Run-time Response Time Control in PLC-based Real-Time Systems using Reinforcement Learning
RISE - Research Institutes of Sweden, ICT, SICS.
RISE - Research Institutes of Sweden, ICT, SICS.ORCID iD: 0000-0002-1512-0844
RISE - Research Institutes of Sweden, ICT, SICS.ORCID iD: 0000-0001-7879-4371
RISE - Research Institutes of Sweden, ICT, SICS.ORCID iD: 0000-0003-1597-6738
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Timing requirements such as constraints on response time are key characteristics of real-time systems and violations of these requirements might cause a total failure, particularly in hard real-time systems. Runtime monitoring of the system properties is of great importance to check the system status and mitigate such failures. Thus, a runtime control to preserve the system properties could improve the robustness of the system with respect to timing violations. Common control approaches may require a precise analytical model of the system which is difficult to be provided at design time. Reinforcement learning is a promising technique to provide adaptive model-free control when the environment is stochastic, and the control problem could be formulated as a Markov Decision Process. In this paper, we propose an adaptive runtime control using reinforcement learning for real-time programs based on Programmable Logic Controllers (PLCs), to meet the response time requirements. We demonstrate through multiple experiments that our approach could control the response time efficiently to satisfy the timing requirements.

Place, publisher, year, edition, pages
2018. p. 217-223
Keywords [en]
adaptive response time contro, lPLC-based real-time programs, reinforcement learning, runtime monitoring
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:ri:diva-34197DOI: 10.1145/3194133.3194153Scopus ID: 2-s2.0-85051555083ISBN: 9781450357159 (print)OAI: oai:DiVA.org:ri-34197DiVA, id: diva2:1232996
Conference
13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Available from: 2018-07-13 Created: 2018-07-13 Last updated: 2019-04-05Bibliographically approved

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Saadatmand, MehrdadBorg, MarkusBohlin, Markus

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • en-GB
  • en-US
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  • Other locale
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Output format
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