A compositional modelling and analysis framework for stochastic hybrid systems
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 aspect...
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| Published in | Formal methods in system design Vol. 43; no. 2; pp. 191 - 232 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Boston
Springer US
01.10.2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-9856 1572-8102 |
| DOI | 10.1007/s10703-012-0167-z |
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| 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. |
|---|---|
| AbstractList | 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. 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 languageawhich is originally designed for stochastic timed systems without complex continuous aspectsathat 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. |
| Author | Hermanns, Holger Hahn, Ernst Moritz Katoen, Joost-Pieter Hartmanns, Arnd |
| Author_xml | – sequence: 1 givenname: Ernst Moritz surname: Hahn fullname: Hahn, Ernst Moritz organization: Saarland University – Computer Science – sequence: 2 givenname: Arnd surname: Hartmanns fullname: Hartmanns, Arnd email: arnd@cs.uni-saarland.de organization: Saarland University – Computer Science – sequence: 3 givenname: Holger surname: Hermanns fullname: Hermanns, Holger organization: Saarland University – Computer Science – sequence: 4 givenname: Joost-Pieter surname: Katoen fullname: Katoen, Joost-Pieter organization: LS2: Software Modelling and Verification, RWTH Aachen University |
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| Keywords | Modelling Abstraction Analysis Stochastic hybrid automata Process calculus |
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| Title | A compositional modelling and analysis framework for stochastic hybrid systems |
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