Unified Graphical Co-modelling of Cyber-Physical Systems Using AADL and Simulink/Stateflow

Zhan, Haolan; Lin, Qianqian; Wang, Shuling; Talpin, Jean-Pierre; Xu, Xiong; Zhan, Naijun

doi:10.1007/978-3-030-31038-7_6

Cited by 8 publications

(8 citation statements)

References 35 publications

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“…2.1). The generated C code is of 3500-4000 lines, longer than the C code (about 2500 lines) generated by [39] (Sect. 2.1).…”

Section: Verification For Hcspmentioning

confidence: 89%

“…At the software layer, it consists of three threads with different priorities, which are scheduled according to the scheduling policy specified by the Processor. The simulation of this combined model can be found in [39].…”

Section: Physical Layermentioning

confidence: 99%

“…2.1). One major reason is that the generated C code in this paper is approximately bisimilar to the original AADL ⊕ S/S model of ACCS, which means the detailed behaviours of ACCS are reflected in the C code and vice versa, while it is not the case for [39] where no such bisimulation can be guaranteed.…”

Section: Verification For Hcspmentioning

confidence: 99%

“…Most significantly, it incorporates the combination of AADL and Simulink/Stateflow (AADL⊕S/S) in [35], and the co-simulation of combined AADL⊕S/S models by translation to C code and defining their integration [39]. Other additions include a simulation tool for HCSP described in [39], and translation procedures from Simulink and Stateflow models into HCSP programs whose results are easier to understand and verify, as well as supporting more features (the procedure for Stateflow is described in [15], and the one for Simulink will be described in this paper). Finally, formal verification tools are significantly improved [31], and a new code generation process to C is added.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

MARS: A Toolchain for Modelling, Analysis and Verification of Hybrid Systems

Chen¹,

Han²,

Tang³

et al. 2017

NASA Monographs in Systems and Software Engineering

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We introduce Mars 2.0 for modeling, analysis, verification and code generation of Cyber-Physical Systems. Mars 2.0 integrates Mars 1.0 with several important extensions and improvements, allowing the design of cyber-physical systems using the combination of AADL and Simulink/Stateflow (AADL⊕S/S), which provide a unified graphical framework for modeling the functionality, physicality and architecture of the system to be developed. For a safety-critical system, formal analysis and verification of its combined AADL⊕S/S model can be conducted via the following steps. First, the toolchain automatically translates AADL ⊕ S/S models into Hybrid CSP (HCSP), an extension of CSP for formally modeling hybrid systems. Second, the HCSP processes can be simulated using the HCSP simulator, and to complement incomplete simulation, they can be verified using the Hybrid Hoare Logic prover in Isabelle/HOL, as well as the more automated HHLPy prover. Finally, implementations in SystemC or C can be automatically generated from the verified HCSP processes. The transformation from AADL⊕S/S to HCSP, and the one from HCSP to SystemC or C, are both guaranteed to be correct with formal proofs. This approach allows model-driven design of safety-critical cyber-physical systems based on graphical and formal models and proven-correct translation procedures. We demonstrate the use of the toolchain on several benchmarks of varying complexity, including several industrial-sized examples.CCS Concepts: • Software and its engineering → Formal software verification; Semantics; • Computer systems organization → Embedded software.

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“…2.1). The generated C code is of 3500-4000 lines, longer than the C code (about 2500 lines) generated by [39] (Sect. 2.1).…”

Section: Verification For Hcspmentioning

confidence: 89%

Section: Physical Layermentioning

confidence: 99%

Section: Verification For Hcspmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

MARS: A Toolchain for Modelling, Analysis and Verification of Hybrid Systems

Chen¹,

Han²,

Tang³

et al. 2017

NASA Monographs in Systems and Software Engineering

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“…Table 1 presents tools and environments available for the simulation of a hybrid automaton model for HDSs. Simulink and Stateflow, which are interactive tools of the very popular technical computing environment MATLAB, are extensively used for modeling and simulating hybrid automata [19]- [21]. Simulink is a tool for the modeling and simulation of nonlinear dynamic systems, and with Stateflow, it is possible to model complex hierarchical state machines.…”

Section: Numerical Simulation Of Hybrid Automatamentioning

confidence: 99%

Modeling and simulation of the two-tank system within a hybrid framework

Yaakoubi

Haggège

2023

IJECE

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<p><span lang="EN-US">Most real-world dynamical systems are often involving continuous behaviors and discrete events, in this case, they are called hybrid dynamical systems (HDSs). To properly model this kind of systems, it is necessary to consider both the continuous and the discrete aspects of its dynamics. In this paper, a modeling framework based on the hybrid automata (HA) approach is proposed. This hybrid modeling framework allows combining the multi-state models of the system, described by nonlinear diﬀerential equations, with the system’s discrete dynamics described by ﬁnite state machines. To attest to the efficiency of the proposed modeling framework, its application to a two-tank hybrid system (TTHS) is presented. The TTHS studied is a typical benchmark for HDSs with four operating modes. The MATLAB Simulink and Stateflow tools are used to implement and simulate the hybrid model of the TTHS. Different simulations results demonstrate the efficiency of the proposed modeling framework, which allows us to appropriately have a complete model of an HDS.</span></p>

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