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Applying DEVS modeling for discrete event multiple model control of a time varying plant

Published: 03 December 2006 Publication History

Abstract

In recent years, we have developed a Modeling and Simulation-Driven Engineering methodology for engineering embedded Real-Time systems. This approach relies on the use of the DEVS formalism for developing components of real-time embedded systems using incremental development. Here, we show how to apply these techniques for an application in hybrid control. The model defines a discreteevent controller for a time varying plant based on multiple model control. Our discrete event approach permitted us to define such application, seamlessly integrating discrete event and continuous components. The approach allows secure, reliable testing, analysis of different levels of abstraction in the system, and model reuse. The common problem of "controller wind-up" or "parameter estimation bursting" can be avoided when performing this proposed form of discrete event adaptive control.

References

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Campbell, A. 2005. Improvements to Stochastic Multiple Model Control: Hypothesis Test Switching and a Modified Model Arrangement. M.A.Sc. Thesis. Carleton University, Canada. August.
[2]
Glinsky, E.; and G. Wainer. 2004. Modeling and simulation of systems with hardware-in-the-loop. In Proceedings of the Winter Simulation Conference. Washington, DC. IEEE Press.
[3]
Glinsky, E.; and G. B. Wainer. 2004. Model-Based Development of Embedded Systems with RT-CD++. In Proceedings of the WIP session, IEEE Real-Time and Embedded Technology and Applications Symposium. Toronto, ON. Canada.
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Kofman, E. 2003. Discrete Event Based Simulation and Control of Continuous Systems. Ph.D. Thesis. Universidad Nacional de Rosario, Argentina. August.
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Kofman, E. 2003b. Quantized-State Control. A Method for Discrete Event Control of Continuous Systems, Latin American Applied Research (LAAR Journal), 33(4). pp 399--406.
[6]
Kofman, E. 2003c. Discrete Event Control of Time Varying Plants, Technical Report LSD0303, LSD, Universidad Nacional de Rosario.
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Narendra, K. S., O. A. Driollet, M. Feiler, and K. George. 2003. Adaptive control using multiple models, switching and tuning, Int. J. Adapt. Control Signal Process., vol. 17, pp. 87--102.
[8]
Wainer, G. 2002. CD++: a toolkit to define discrete-event models. Software, Practice and Experience. Wiley. Vol. 32, No. 3. pp. 1261--1306.
[9]
Wainer, G.; E. Glinsky, and P. MacSween. 2005. Model-Driven Architecture of Real-Time Systems. In Modeldriven Software Development - Volume II of Research and Practice in Software Engineering. S. Beydeda and V. Gruhn eds., Springer-Verlag.
[10]
Zeigler, B. 2005. Continuity and Change (Activity) are Fundamentally Related in DEVS Simulation of Continuous Systems, LNCS, Vol. 3397, Springer-Verlag.
[11]
Zeigler, B. 1998. DEVS. Theory of Quantization. DARPA Contract N6133997K-007. University of Arizona.
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Zeigler, B; T. Kim, and H. Praehofer. 2000. Theory of M&S. New York.

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Published In

cover image ACM Conferences
WSC '06: Proceedings of the 38th conference on Winter simulation
December 2006
2429 pages
ISBN:1424405017

Sponsors

  • IIE: Institute of Industrial Engineers
  • ASA: American Statistical Association
  • IEICE ESS: Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
  • IEEE-CS\DATC: The IEEE Computer Society
  • SIGSIM: ACM Special Interest Group on Simulation and Modeling
  • NIST: National Institute of Standards and Technology
  • (SCS): The Society for Modeling and Simulation International
  • INFORMS-CS: Institute for Operations Research and the Management Sciences-College on Simulation

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Winter Simulation Conference

Publication History

Published: 03 December 2006

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WSC06
Sponsor:
  • IIE
  • ASA
  • IEICE ESS
  • IEEE-CS\DATC
  • SIGSIM
  • NIST
  • (SCS)
  • INFORMS-CS
WSC06: Winter Simulation Conference 2006
December 3 - 6, 2006
California, Monterey

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WSC '06 Paper Acceptance Rate 177 of 252 submissions, 70%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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