article

A compositional modelling and analysis framework for stochastic hybrid systems

Authors:

Ernst Moritz Hahn,

Arnd Hartmanns,

Holger Hermanns,

Joost-Pieter KatoenAuthors Info & Claims

Formal Methods in System Design, Volume 43, Issue 2

Pages 191 - 232

https://doi.org/10.1007/s10703-012-0167-z

Published: 01 October 2013 Publication History

Abstract

The theory of hybrid systems is well-established as a model for real-world systems consisting of continuous behaviour and discrete control. In practice, the behaviour of such systems is also subject to uncertainties, such as measurement errors, or is controlled by randomised algorithms. These aspects can be modelled and analysed using stochastic hybrid systems. In this paper, we present HModest, an extension to the Modest modelling language--which is originally designed for stochastic timed systems without complex continuous aspects--that adds differential equations and inclusions as an expressive way to describe the continuous system evolution. Modest is a high-level language inspired by classical process algebras, thus compositional modelling is an integral feature. We define the syntax and semantics of HModest and show that it is a conservative extension of Modest that retains the compositional modelling approach. To allow the analysis of HModest models, we report on the implementation of a connection to recently developed tools for the safety verification of stochastic hybrid systems, and illustrate the language and the tool support with a set of small, but instructive case studies.

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cover image Formal Methods in System Design

Formal Methods in System Design Volume 43, Issue 2

October 2013

247 pages

ISSN:0925-9856

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Copyright © Copyright © 2013 Springer Science+Business Media New York.

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Kluwer Academic Publishers

United States

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Published: 01 October 2013

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https://dl.acm.org/doi/10.1145/3641513.3651399
Nejati APrakash Nayak SSchmuck A(2024)Context-triggered Games for Reactive Synthesis over Stochastic Systems via Control Barrier CertificatesProceedings of the 27th ACM International Conference on Hybrid Systems: Computation and Control10.1145/3641513.3650136(1-12)Online publication date: 14-May-2024
https://dl.acm.org/doi/10.1145/3641513.3650136
Junges SÁbrahám EHensel CJansen NKatoen JQuatmann TVolk M(2024)Parameter synthesis for Markov models: covering the parameter spaceFormal Methods in System Design10.1007/s10703-023-00442-x62:1-3(181-259)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10703-023-00442-x
Wooding BLavaei A(2024)IMPaCT: nterval DP rallel Construction for ontroller Synthesis of Large-Scale Sochastic SystemsQuantitative Evaluation of Systems and Formal Modeling and Analysis of Timed Systems10.1007/978-3-031-68416-6_15(249-267)Online publication date: 10-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-68416-6_15
Da Silva CSchupp SRemke A(2023)Optimizing Reachability Probabilities for a Restricted Class of Stochastic Hybrid Automata via Flowpipe ConstructionACM Transactions on Modeling and Computer Simulation10.1145/360719733:4(1-27)Online publication date: 26-Oct-2023
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Willemsen LRemke AÁbrahám E(2023)Comparing Two Approaches to Include Stochasticity in Hybrid AutomataQuantitative Evaluation of Systems10.1007/978-3-031-43835-6_17(238-254)Online publication date: 20-Sep-2023
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Delicaris JSchupp SÁbrahám ERemke A(2023)Maximizing Reachability Probabilities in Rectangular Automata with Random ClocksTheoretical Aspects of Software Engineering10.1007/978-3-031-35257-7_10(164-182)Online publication date: 4-Jul-2023
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Ye KCavalcanti AFoster SMiyazawa AWoodcock J(2022)Probabilistic modelling and verification using RoboChart and PRISMSoftware and Systems Modeling (SoSyM)10.1007/s10270-021-00916-821:2(667-716)Online publication date: 1-Apr-2022
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Adelt JHerber PNiehage MRemke A(2022)Towards Safe and Resilient Hybrid Systems in the Presence of Learning and UncertaintyLeveraging Applications of Formal Methods, Verification and Validation. Verification Principles10.1007/978-3-031-19849-6_18(299-319)Online publication date: 22-Oct-2022
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Hartmanns AKlauck M(2022)The Modest State of Learning, Sampling, and Verifying StrategiesLeveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning10.1007/978-3-031-19759-8_25(406-432)Online publication date: 22-Oct-2022
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