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Relevant bibliographies by topics / Simulation of dynamic systems

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Journal articles

Academic literature on the topic 'Simulation of dynamic systems'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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Journal articles on the topic "Simulation of dynamic systems"

1

Alzbutas, R., and V. Janilionis. "THE SIMULATION OF DYNAMIC SYSTEMS USING COMBINED MODELLING." Mathematical Modelling and Analysis 5, no. 1 (2000): 7–17. http://dx.doi.org/10.3846/13926292.2000.9637123.

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The new approach to the problems of dynamic systems simulation is proposed. The analytical and imitation modelling of non‐linear complex dynamic systems which comprise simulation of continuous and discrete processes with constant and variable parameters, are investigated. The aggregate mathematical modelling scheme [1] and the method of control sequences for discrete systems specification and simulation are used as well as the dynamic mathematical modelling scheme for continuous process formalization and modelling. According to them the investigated systems are presented as the set of interacting piecewise linear aggregates, which can include processes described with differential equations. The above mentioned approach is used in developing software for the construction and research of the models. The modelling of the dynamic systems’ control is also analyzed and developed software for the dynamic systems’ simulation is presented. It is related to the proposed combined modelling methodology. The developed dynamical simulation system ADPRO (Automatic Differentiation PROgram) extends applicability of the system SIMAS (SIMulation of the Aggregate Systems) [2] with dynamical simulation means realized with APL2 (A Programming Language 2) and based on automatic differentiation [3]. The created model of service process and its control can be used as a base for other models of wide class complex dynamics’ systems [4], the parts of which are described with differential equations.

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2

Rükgauer, A., and W. Schiehlen. "Simulation of modular dynamic systems." Mathematics and Computers in Simulation 46, no. 5-6 (1998): 535–42. http://dx.doi.org/10.1016/s0378-4754(98)00082-2.

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3

Toby, Sidney, and Frina S. Toby. "The Simulation of Dynamic Systems." Journal of Chemical Education 76, no. 11 (1999): 1584. http://dx.doi.org/10.1021/ed076p1584.

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4

Alzbutas, Robertas, and Vytautas Janilionis. "Dynamic systems simulation using APL2." ACM SIGAPL APL Quote Quad 29, no. 2 (1998): 20–25. http://dx.doi.org/10.1145/379277.312699.

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5

Nishitani, Hirokazu, Eiichi Kunugita, Yuan-Chen Wan, and Masahiro Kujime. "Dynamic simulation of large systems." KAGAKU KOGAKU RONBUNSHU 17, no. 1 (1991): 149–56. http://dx.doi.org/10.1252/kakoronbunshu.17.149.

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6

Skelton, Robert E., Fa Ming Li, and Mauricio de Oliveira. "Optimal Simulation for Large Dynamic Systems." Advances in Science and Technology 56 (September 2008): 147–53. http://dx.doi.org/10.4028/www.scientific.net/ast.56.147.

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Like most engineering design problems, simulation design for large dynamic systems should seek a trade- o® between performance and cost. Here the perfor- mance is de¯ned by simulation accuracy; and the cost is related to computational resource, measured by the total wordlength. The simulation accuracy depends on model complexity, model realization and computational implementation. The optimal simula- tion problem is to determine all these factors to en- sure desired accuracy with available computational resource. When computational cost is the primary concern, one can minimize the computational re- source with simulation accuracy constraint. We de- ¯ne the economical simulation problem (ESP) as de- signing the simulation of a stable linear system and distributing computational resources (wordlength) among the digital devices such that the computa- tional cost(memory) is minimized without violat- ing the required simulation accuracy. This problem is generally not convex because of the scaling con- straint. By exploring the special structure of this joint optimization of the choice of the realizations and the computational resources to be applied, and under a scaling assumption, the ESP is converted to a convex problem. Numerical results are given which compare this method with existing approaches.

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7

Bhatti, Muhammad Akram, Li Chang Xi ., and Ye lin . "Modeling and Simulation of Dynamic Systems." Journal of Applied Sciences 6, no. 4 (2006): 950–54. http://dx.doi.org/10.3923/jas.2006.950.954.

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8

Deckmann, S. M., V. F. da Costa, and D. A. Alves. "Dynamic Simulation for Interconnected Power Systems." IFAC Proceedings Volumes 18, no. 7 (1985): 261–68. http://dx.doi.org/10.1016/s1474-6670(17)60444-0.

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9

Lubachevsky, Boris D. "Fast simulation of multicomponent dynamic systems." Bell Labs Technical Journal 5, no. 2 (2002): 134–56. http://dx.doi.org/10.1002/bltj.2227.

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10

Rosenberg, Ronald C., Joseph Whitesell, and John Reid. "Extendible simulation software for dynamic systems." SIMULATION 58, no. 3 (1992): 175–83. http://dx.doi.org/10.1177/003754979205800307.

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