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Model Transformation Tools (MTT): The Open Source Bond Graph Project

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Abstract

The rapid growth of GNU/Linux in recent years has focused attention on free and open source software. MTT (Model Transformation Tools) is, as far as the authors are aware, the only open source project related to bond graphs. This paper surveys MTT in its present form and invites collaboration from the wider bond graph community.

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... The bond graph model of Figure 5 with reaction kinetics defined by Equation (53) was compiled into ordinary differential equations using the bond graph software MTT (model transformation tools) [32]. Free energy constants were obtained using the methods of § 3.1 and the kinetic parameters were derived as in § 3.2. ...
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The bond graph approach to modelling biochemical networks is extended to allow hierarchical construction of complex models from simpler components. This is made possible by representing the simpler components as thermodynamically open systems exchanging mass and energy via ports. A key feature of this approach is that the resultant models are robustly thermodynamically compliant: the thermodynamic compliance is not dependent on precise numerical values of parameters. Moreover, the models are reusable due to the well-defined interface provided by the energy ports. To extract bond graph model parameters from parameters found in the literature, general and compact formulae are developed to relate free-energy constants and equilibrium constants. The existence and uniqueness of solutions is considered in terms of fundamental properties of stoichiometric matrices. The approach is illustrated by building a hierarchical bond graph model of glycogenolysis in skeletal muscle.
... Bond graph approaches have also developed considerably in recent years, in particular through the development of computational tools for their analysis, graphical construction and manipulation, and modularity and reuse [33][34][35][36][37][38], which are key preoccupations for systems biology and physiome modelling. Our focus is on how kinetics and thermodynamic properties of biochemical reactions can be represented in this framework, and how the bond graph formalism allows key properties to be calculated from this representation. ...
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Thermodynamic aspects of chemical reactions have a long history in the Physical Chemistry literature. In particular, biochemical cycles - the building-blocks of biochemical systems - require a source of energy to function. However, although fundamental, the role of chemical potential and Gibb's free energy in the analysis of biochemical systems is often overlooked leading to models which are physically impossible. The bond graph approach was developed for modelling engineering systems where energy generation, storage and transmission are fundamental. The method focuses on how power flows between components and how energy is stored, transmitted or dissipated within components. Based on early ideas of network thermodynamics, we have applied this approach to biochemical systems to generate models which automatically obey the laws of thermodynamics. We illustrate the method with examples of biochemical cycles. We have found that thermodynamically compliant models of simple biochemical cycles can easily be developed using this approach. In particular, both stoichiometric information and simulation models can be developed directly from the bond graph. Furthermore, model reduction and approximation while retaining structural and thermodynamic properties is facilitated. Because the bond graph approach is also modular and scaleable, we believe that it provides a secure foundation for building thermodynamically compliant models of large biochemical networks.
... They can show causality and detail in both the manner and type of interactions between subsystems and components. They provide a symbolic representation of a system from which other representations can be derived such as state space equations, differentiable algebraic equations, state-space matrices, transfer functions, frequency responses and so on (Ballance et al., 2005). At the conceptual level, a word bond graph is used to provide a top-level representation of the system. ...
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The design trade space of a complex system is vast, and overlooking potential architecture alternatives can have an adverse impact on the final outcome. This paper presents a Smart Systems Architecting (SSA) approach for generating and assessing architecture alternatives. Computationally intelligent techniques such as Evolutionary Algorithms (EA) are used to explore the design trade space for candidate architectures. A novel fuzzy architecture assessment approach is presented to quantitatively evaluate the set of possible solutions based on the decision-maker's preferences even in the presence of incomplete, subjective and ambiguous information. The broad applicability of Smart Systems Architecting is demonstrated by three specific approaches to fuzzy evolutionary search at different levels of design ambiguity.
... Other software tools have been developed that model systems using bond graph. A representative list includes 20-sim [12], DYMOLA [13], MS1 [14], KALIBOND [15], SYMBOLS 2000 [16], BGML [17], BONK [18], MTT [19], BG_V 20e [20] and BGTOOLS [21]. ...
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Bond graph is an apt modelling tool for any system working across multiple energy domains. Power electronics system modelling is usually the study of the interplay of energy in the domains of electrical, mechanical, magnetic and thermal. The usefulness of bond graph modelling in power electronic field has been realised by researchers. Consequently in the last couple of decades, there has been a steadily increasing effort in developing simulation tools for bond graph modelling that are specially suited for power electronic study. For modelling rotating magnetic fields in electromagnetic machine models, a support for vector variables is essential. Unfortunately, all bond graph simulation tools presently provide support only for scalar variables. We propose an approach to provide complex variable and vector support to bond graph such that it will enable modelling of polyphase electromagnetic and spatial vector systems. We also introduced a rotary gyrator element and use it along with the switched junction for developing the complex/vector variable/s toolbox. This approach is implemented by developing a complex S-function tool box in Simulink inside a MATLAB environment. This choice has been made so as to synthesise the speed of S-function, the user friendliness of Simulink and the popularity of MATLAB.
Chapter
The previous chapters presented the fundamentals of bond graph methodology and its potential in tackling some basic problems in various application areas, e.g. models of variable structure (Chapter 7), lumped parameter approximation of distributed parameter models (Chapter 9), and open thermodynamic systems (Chapter 10). The questions this chapter attempts to answer are: how can software support bond graphbased physical systems modelling and in which phases of the modelling process can it do so. Before going into details, an important general observation has to be pointed out.
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A bond graph framework giving a unified treatment of both physical-model based control and hybrid experimental–numerical simulation (also known as real-time dynamic substructuring) is presented. The framework consists of two subsystems, one physical and one numerical, connected by a transfer system representing non-ideal actuators and sensors. Within this context, a two-stage design procedure is proposed: firstly, design and/or analysis of the numerical and physical subsystem interconnection as if the transfer system were not present; and secondly removal of as much as possible of the transfer system dynamics while having regard for the stability margins established in the first stage. The approach allows the use of engineering insight backed up by well-established control theory; a number of possibilities for each stage are given. The approach is illustrated using two laboratory systems: an experimental mass-spring-damper substructured system and swing up and hold control of an inverted pendulum. Experimental results are provided in the latter case.
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The paper proposes a novel XML based format called BGML that aims at supporting the exchange and the reuse of bond graph models of engineering systems between various bond graph and non-bond graph software. The validity of a BGML description of a bond graph model can be verified against an XML schema. Model equations and constitutive relations (linear or not) are represented in MathML. The concept of BGML is illustrated by means of a small example. In order to demonstrate the usefulness of BGML, an approach to transformations of formats used by bond graph software from and to XML and an export to non-bond graph software, as well as prototypes of their implementation in an experimental open source modelling and simulation environment are discussed.
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Much of the current body of control achieves a generic coverage of application areas by having a generic representation of the systems to be controlled. Instead of having a generic representation of systems, we propose a generic method for automatically deriving system-specific representations. We call this approach metamodelling and we use the Bond-Graph representation as a basis for this. This allows the use of particular representations for particular (possibly partially -known, possibly non-linear) systems. In this paper we illustrate the use of the bond graph representation by introducing one aspect of our approach to model-based control namely model-based observer control. The motivation for this approach comes from three areas: linear state-space observer theory, inferential control, and the application of bond graphs to observer design. An example related to process engineering is used to demonstrate the basic ideas.
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Analysis and simulation of non-linear inverse systems are sometimes necessary in the design of control systems particularly when trying to determine an input control required to achieve some predefined output specifications. But unlike physical systems which are proper, the inverse systems are very often improper leading to numerical problems in simulation as their models sometimes have a high index when written in the form of differential-algebraic equations (DAE). This paper provides an alternative approach whereby performance specifications and the physical system are combined within a single bond graph leading to a greatly simplified simulation problem.
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A new bond graph framework for sensitivity theory is applied to model-based predictive control, state estimation, and parameter estimation in the context of physical systems. The approach is illustrated using a nonlinear mechatronic system.
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A bond-graph based approach to design in the physical domain is described which uses the concept of virtual actuators and virtual sensors. The approach is illustrated by, and implemented on, an experimental ball and beam system.
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Conventional bond graph theory is predicated on the notion that a bond has a single causal stroke: an effort imposed at one end implies a flow imposed at the other. This notion is implied by components having a known constitutive relationship. This paper discusses bond graphs with two causal strokes - Bicausal bond-graphs. These can, for example, handle systems with unknown parameters. This paper addresses issues arising from the general idea of inverse systems - physical systems with a non-standard input-output pattern; in particular: dynamic inverses, parameter estimation and state estimation. 1. Introduction r v 1 i 1 c v c Fig. 1. An electrical circuit 1 R C S e 0 i 1 v 1 v c i 1 Fig. 2. An electrical circuit: bond graph Consider the linear time invariant electrical circuit of Figure 1 and the associated Bond Graph of Figure 2. In addition to the qualitative description of the system structure implied by the Bond Graph of Figure 2, there is quantitative info...
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