Applying Timed Interval Calculus to Simulink Diagrams

Chen, Chunqing; Dong, Jin Song

doi:10.1007/11901433_5

Cited by 11 publications

(10 citation statements)

References 15 publications

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“…The work reported in [11] is close to the works of CLawZ [18] and Circus [10] with respect to proposing a systematic translation from Simulink into some formal language. But [11] defines a new language based on time intervals.…”

Section: Related Workmentioning

confidence: 87%

“…But [11] defines a new language based on time intervals. These works differ from ours because they use theorem proving.…”

Section: Related Workmentioning

confidence: 99%

“…We identified several related works [11,18,10,3,19,20] that aim to guarantee correctness of control systems. However, none of these works have considered a systematic translation from Simulink to CSP , based on compositional rules, nor the influence of architectural requirements on the system in a formal way.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, we are indeed giving a semantics to Simulink via a mapping into CSP . The proposed semantics is based on the informal descriptions provided in the Simulink manuals [8], like other works do [10,11].…”

Section: Mapping Control Law Diagrams To Cspmentioning

confidence: 99%

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Architectural Verification of Control Systems Using CSP

Jesus

Mota

Sampaio

et al. 2011

Formal Methods and Software Engineering

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Abstract. Although validation of complex dynamic systems can be realised using checklists and simulations provided by tools such as Simulink, these techniques usually do not cover all system behaviours. Moreover, the control laws are rarely modelled together with the system architecture. This integration can reveal defects which are only detected in final stages of the development. This work presents two major contributions: a strategy to validate the integration of a proposed architecture with control laws, based on the CSP process algebra; and the validation of a Fly-by-wire Elevator Control System designed by Embraer. The results show that the strategy helps finding defects in early stages of the development, saving time and costs.

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Section: Related Workmentioning

confidence: 87%

“…But [11] defines a new language based on time intervals. These works differ from ours because they use theorem proving.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Mapping Control Law Diagrams To Cspmentioning

confidence: 99%

See 2 more Smart Citations

Architectural Verification of Control Systems Using CSP

Jesus

Mota

Sampaio

et al. 2011

Formal Methods and Software Engineering

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“…Collaboration with QinetiQ has established the feasibility and practical relevance of their approach, which is further detailed in [7]. Functional and timing requirements of Simulink diagrams are modelled in [13] using a Timed Interval Calculus (TIC). The technique is based on a translation of Simulink diagrams to TIC specifications, which use the Z mathematical and schema notations to structure interval time properties.…”

Section: Introductionmentioning

confidence: 99%

From control law diagrams to Ada via Circus

Cavalcanti

O'Halloran

2011

Form. Asp. Comput.

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Control engineers make extensive use of diagrammatic notations; control law diagrams are used in industry every day. Techniques and tools for analysis of these diagrams or their models are plentiful; verification of code created to implement them, however, is a challenge that has been taken up by few. Our work is based on industrial tools that produce partial Z and CSP models of discrete-time Simulink diagrams, and on Circus, a notation that combines Z, CSP, and a refinement calculus. We present a strategy to translate Simulink diagrams to Circus, and a strategy to prove that a parallel Ada implementation refines the specification of a diagram; we rely on a Circus semantics for the program. By using a combined notation, we provide a specification that considers both functional and behavioural aspects of a larger set of diagrams, and support verification of a larger number of implementations. We can handle, for instance, arbitrarily large data types and dynamic scheduling.

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