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University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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Integration of Simulink Models with Component-based Software Models

MARIAN, N. See more information about MARIAN, N. on SCOPUS See more information about MARIAN, N. on IEEExplore See more information about MARIAN, N. on Web of Science, TOP, S. See more information about TOP, S. on SCOPUS See more information about TOP, S. on SCOPUS See more information about TOP, S. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (731 KB) | Citation | Downloads: 925 | Views: 3,713

Author keywords
component-based design, model-based design, MATLAB, Simulink, model transformation, discrete-time models, continuous-time models

References keywords
simulink(6), control(6), systems(5), software(4), embedded(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2008-06-02
Volume 8, Issue 2, Year 2008, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2008.02001
Web of Science Accession Number: 000264815000001
SCOPUS ID: 77954668230

Abstract
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Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical constructs and process flow, then software code is generated. A Simulink model is a representation of the design or implementation of a physical system that satisfies a set of requirements. A software component-based system aims to organize system architecture and behaviour as a means of computation, communication and constraints, using computational blocks and aggregates for both discrete and continuous behaviour, different interconnection and execution disciplines for event-based and time-based controllers, and so on, to encompass the demands to more functionality, at even lower prices, and with opposite constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems) is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI), University of Southern Denmark. Once specified, the software model has to be analyzed. One way of doing that is to integrate in wrapper files the model back into Simulink S-functions, and use its extensive simulation features, thus allowing an early exploration of the possible design choices over multiple disciplines. The paper describes a safe translation of a restricted set of MATLAB/Simulink blocks to COMDES software components, both for continuous and discrete behaviour, and the transformation of the software system into the S-functions. The general aim of this work is the improvement of multi-disciplinary development of embedded systems with the focus on the relation between control engineering and software engineering.


References | Cited By  «-- Click to see who has cited this paper

[1] N. Marian, "Model-Based Development of Embedded Software Systems with Components", Advances in Electrical and Computer Engineering Journal, vol. 1/2006, pp. 30-38

[2] Simulink, A tool for modeling, simulation and implementation of control systems [Online] Available: Temporary on-line reference link removed - see the PDF document

[3] M. M. Adams and P. B. Clayton. Clawz, "Cost-effective formal verification for control systems", In 7th International Conference on Formal Engineering Methods, pp. 465-479, 2005.

[4] P. Caspi et al., "Translating Discrete-Time Simulink to Lustre", in Proc. of the 3rd International Embedded Software Conference EMSOFT'03, LNCS 2855, 2003, pp. 1-15
[CrossRef]


[5] N. Scaife et al., "Defining and Translating a "Safe" Subset of Simulink/Stateflow into Lustre", report No TR-2004-16, Verimag, 2004

[6] T. A. Henzinger, C. M. Kirsch and M. A. A. Sanvido, "From Control Models to Real-Time Code Using Giotto", IEEE Control Systems Magazine, Feb. 2003, pp. 50-64
[CrossRef] [SCOPUS Times Cited 84]


[7] A. Agrawl, G. Simon, G. Karsai, "Semantic Translation of Simulink/Stateflow models to Hybrid Automata using Graph Translations", in Electronic Notes in Theoretical Computer Science, vol 109, 2004, pp. 43-56
[CrossRef] [SCOPUS Times Cited 82]


[8] M. Andries, et al., "Graph Transformation for Specification and Programming", Sci. Comput. Program., Vol. 34, No. 1, 1999, pp. 1-5
[CrossRef] [Web of Science Times Cited 67] [SCOPUS Times Cited 98]


[9] IEEE Transactions LaTeX and Microsoft Word Style Files, [Online] Available: Temporary on-line reference link removed - see the PDF document

[10] S. Top, H. J. Norgaard, B. Krogsgaard, B. N. Jorgensen, "The Sandwich Code File Structure - An architectural support for software engineering in simulation based development of embedded control applications", Proceedings of IASTED International Conference on Software Engineering, ACTA Press, 2004

[11] S. Top, H. J. Norgaard, B. N. Jorgensen, "Object oriented C++ programming in SIMULINK - A reengineered simulation architecture for the control algorithm code view", Proceedings of Nordic MATLAB Conference 2003, pp. 79-84

[12] I. Sturmer, D. Travkin,, "Automated Transformation of MATLAB Simulink and Stateflow Models", Proceedings of 4th Workshop on Object-oriented Modeling of Embedded Real-time Systems, 2007, pp. 57-62

References Weight

Web of Science® Citations for all references: 67 TCR
SCOPUS® Citations for all references: 264 TCR

Web of Science® Average Citations per reference: 6 ACR
SCOPUS® Average Citations per reference: 22 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-12-13 07:21 in 32 seconds.




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