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This chapter explores a new way of approximating differential equations, replacing the time discretization by a quantization of the state variables. We shall see that this idea will lead us to discrete event systems in terms of the DEVS formalism instead of difference equations, as in the previous approximations.
Thus, before formulating the numerical methods derived from this approach, we shall introduce the basic definitions of DEVS. This methodology, as a general discrete event systems modeling and simulation formalism, will provide us the tools to describe and translate into computer programs the routines that implement a new family of methods for the numerical integration of continuous systems.
Further, the chapter explores the principles of quantization-based approximations of ordinary differential equations and their representation as DEVS simulation models.
Finally, we shall briefly introduce the QSS method in preparation for the next chapter, where we shall study this numerical method in more detail.
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11.9 References
Hyup Cho and Young Cho. DEVS-C++ Reference Guide. The University of Arizona, 1997.
Jean Baptiste Filippi, Marielle Delhom, and Fabrice Bernardi. The JDEVS Environmental Modeling and Simulation Environment. In Proceedings of IEMSS 2002, volume 3, pages 283–288, Lugano, Switzerland, 2002.
Norbert Giambiasi, Bruno Escude, and Sumit Ghosh. GDEVS: A Generalized Discrete Event Specification for Accurate Modeling of Dynamic Systems. Transactions of SCS, 17(3):120–134, 2000.
Kihyung Kim, Wonseok Kang, and Hyungon Seo. Efficient Distributed Simulation of Hierarchical DEVS Models: Transforming Model Structure into a Non-Hierarchical One. In Proceedings of Annual Simulation Symposium, 2000.
Tag Gon Kim. DEVSim++ User’s Manual. C++ Based Simulation with Hierarchical Modular DEVS Models. Korean Advanced Institute of Science and Technology, 1994. Available at http://www.acims.arizona.edu/.
Ernesto Kofman and Sergio Junco. Quantized State Systems: A DEVS Approach for Continuous System Simulation. Transactions of SCS, 18(3):123–132, 2001.
Ernesto Kofman, Marcelo Lapadula, and Esteban Pagliero. PowerDEVS: A DEVS-based Environment for Hybrid System Modeling and Simulation. Technical Report LSD0306, LSD, UNR, 2003. Submitted to Simulation. Available at http://www.fceia.unr.edu.ar/lsd/powerdevs.
Esteban Pagliero, Marcelo Lapadula, and Ernesto Kofman. PowerDEVS. Una Herramienta Integrada de Simulación por Eventos Discretos. In Proceedings of RPIC03, volume 1, pages 316–321, San Nicolas, Argentina, 2003.
Esteban Pagliero and Marcelo Lapadula. Herramienta Integrada de Modelado y Simulación de Sistemas de Eventos Discretos. Diploma Work. FCEIA, UNR, Argentina, September 2002.
Gabriel Wainer, Gastón Christen, and Alejandro Dobniewski. Defining DEVS Models with the CD++ Toolkit. In Proceedings of ESS2001, pages 633–637, Marseille, France, 2001.
Bernard Zeigler, Tag Gon Kim, and Herbert Praehofer. Theory of Modeling and Simulation. Second edition. Academic Press, New York, 2000.
Bernard Zeigler and Jong Sik Lee. Theory of Quantized Systems: Formal Basis for DEVS/HLA Distributed Simulation Environment. In SPIE Proceedings, pages 49–58, 1998.
Bernard Zeigler and Hessam Sarjoughian. Introduction to DEVS Modeling and Simulation with JAVA: A Simplified Approach to HLA-Compliant Distributed Simulations. Arizona Center for Integrative Modeling and Simulation. Available at http://www.acims.arizona.edu/.
Bernard Zeigler. Theory of Modeling and Simulation. John Wiley & Sons, New York, 1976.
11.10 Bibliography
Christos Cassandras. Discrete Event Systems: Modeling and Performance Analysis. Irwin and Aksen, 1993.
Ernesto Kofman. Discrete Event Simulation and Control of Continuous Systems. PhD thesis, Universidad Nacional de Rosario, Rosario, Argentina, 2003.
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(2006). Discrete Event Simulation. In: Continuous System Simulation. Springer, Boston, MA. https://doi.org/10.1007/0-387-30260-3_11
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DOI: https://doi.org/10.1007/0-387-30260-3_11
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