Bibliography of bond graph theory and application

Breedveld, Pieter C.; Rosenberg, Ronald; Zhou, Tong

doi:10.1016/0016-0032(91)90069-f

Cited by 60 publications

(20 citation statements)

References 3 publications

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“…This technique was further developed by Karnopp and Rosenberg (Karnopp et al, 1990;Karnopp & Rosenberg, 1968;Rosenberg & Karnopp, 1983). Several books, special issues and articles on bond graph technique have popularised it for growing usage (Borutzky, 2009;Borutzky et al, 2004;Breedveld, 1984;1991;2004;Breedveld et al, 1991;Cellier et al, 1995;Dauphin-Tanguy, 2000;Gawthrop, 1995;Gawthrop & Smith, 1996;Mukherjee & Karmakar, 2000;Thoma, 1990;Thoma & Perelson, 1976).…”

Section: Analogous Behaviour Of Physical Systemsmentioning

confidence: 99%

S-Function Library for Bond Graph Modeling

Umesh¹

2012

Technology and Engineering Applications of Simulink

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IntroductionS-functions are short for system-functions. They are used for extending the capabilities of Simulink ® . S-functions allows us to add our own algorithms to Simulink models. The process of creating S-function blocks is quite simple. Simulink provides a S-function API which can be used to write a S-function routine observing a set of laid down rules. The compiled routine is enclosed inside a Simulink block, which can be subsequently customised by masking. A library of customised S-function blocks are created for an application specific task. This library can be subsequently distributed to work in MATLAB ® environment. How is S-function useful?S-function can also be described as a computer language description of the Simulink block. S-function is written in any one of the popular languages viz C, C++, Fortran or Ada besides MATLAB's own M programming language and compiled as MEX files, where MEX stands for MATLAB Executable. S-functions use a special calling syntax called the S-function API that interacts with the Simulink engine. This interaction is very similar to the interaction that takes place between the engine and built-in Simulink blocks.In MATLAB S-functions, the S-function routines are implemented as MATLAB functions. In C MEX S-functions, they are implemented as C functions. All the S-function routines available to MATLAB S-functions exist for C MEX S-functions as well. However, Simulink provides a larger set of S-function routines for C MEX S-functions.S-function routines can be written for continuous, discrete or hybrid systems. A set of S-function blocks created by us can be placed in a tool box or library and distributed for working in MATLAB environment. S-functions allow creation of customised blocks for Simulink. By following a set of rules, any block algorithms can be implemented in an S-function. It can also be deployed for using an existing C code into a simulation. After compiling the S-function, the run time file has to be placed in an S-function block. User interface can then be customised by using masking. An advantage of using S-functions is that a general purpose block can be built that can be used many times in a model, varying parameters with each instance of the block.The most common usage of S-functions is for creating a set of custom Simulink blocks for an application. Existing C code in the application is easily encapsulated into S-function block and used as a separate Simulink block. This is used alongside the other blocks of Simulink.

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Section: Analogous Behaviour Of Physical Systemsmentioning

confidence: 99%

S-Function Library for Bond Graph Modeling

Umesh¹

2012

Technology and Engineering Applications of Simulink

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“…However, there exist a couple of excellent textbooks, surveys and bibliographies that make the search for literature quite straightforward. On biographies the one of Breedveld and Rosenberg summarize the development up to 1991 nicely (Breedveld et al (1991)). Another extensive source is currently available at the web site of Francoise Cellier (http://www.ece.arizona.edu/ cellier/).…”

Section: Bond Graphs and Its Derivativesmentioning

confidence: 99%

Modelling: Compartmental networks and topologies a comparison with bond graphs

Preisig¹

2004

Computer Aided Chemical Engineering

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Compartmental network modelling is compared with the bond graph approach. Whilst both approaches build on the conservation principle, the compartmental network approach is on a slightly higher level and more compact. Also no analogies must be used, the concepts of physics are used directly in connection whilst system theoretical arguments define consistency and solvability, being roughly equivalent to causality in bond graphs.Keywords: modelling, mechanistic, first principle, Bond Graphs ScopeThe author looks back to somewhere around 20 years of research in computer-aided modelling, which resulted in a methodological approach to modelling of physical-chemicalbiological systems implemented now in the third generation as a tool we call Modeller (Westerweele (2003)). The method builds on a compartmental network modelling approach and in the course of the last few years the question of the relation of this network approach with the bond graph approach has been raised a couple of times. Thus this paper is trying to illuminate some of the main differences. The views being reflected are personal and may not be shared by the bond graph specialist as both approaches are rather much building on macroscopic physics, meaning that the quantisation of matter and energy is not of relevance, but that it deals in general with a larger time scale and field theory applies in its full scope. It should be noted that modelling is here limited to defining a set of differential algebraic equations describing the behaviour of natural systems 1 . Compartmental Network ModellingThe approach is based on splitting the relevant piece of the world into a set of communicating control volume. Thus we define a basic model topology as a mapping of the real world object into a network of primitive systems that can store EXTENSIVE CAPACITIES and CONNECTIONS, which can transfer extensive quantities. This topology we call the PHYSICAL TOPOLOGY, as it represents the physical containment of the process. This first step cannot be automated. * e-mail: Heinz.Preisig@chemeng.ntnu.no 1 The limitation to natural is not necessary, but the extension is also not of relevance to this discussion.

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“…Models of complex systems are built as a collection of the basic elements and a network of relations that are derived from the representation. Furthermore, we can take advantage of the work on bond graphs performed by others [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Application of Bond Graph Models to Economics

Wong

2001

International Journal of Modelling and Simulation

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As a qualitative and quantitative knowledge representation model, bond graphs comply with desirable features of modelling in the AI perspective. They allow for local, modular model construction and can be extended to full numerical detail. They are also generic for a large class of systems. This paper argues for bond graph modelling as a qualitative reasoning technique. Numerical information can be incorporated into the bond graph representations so that numerical simulations are also possible. Bond graph modelling is applied to economic system simulation for integrating qualitative and quantitative approaches, and then modified and applied to economic systems through a qualitative simulation package.

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Bibliography of bond graph theory and application

Cited by 60 publications

References 3 publications

S-Function Library for Bond Graph Modeling

S-Function Library for Bond Graph Modeling

Modelling: Compartmental networks and topologies a comparison with bond graphs

Application of Bond Graph Models to Economics

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