Basic Forms of Model Representation
The solution of complex, real-world problems is based on modelling. A model simplifies the system of interest by abstracting some subset of its observable attributes. This focuses attention on those features of the system relevant to the problem of intere
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1.1 Objectives The solution of complex, real-world problems is based on modelling. A model simplifies the system of interest by abstracting some subset of its observable attributes. This focuses attention on those features of the system relevant to the problem of interest, and excludes others deemed not to be of direct relevance to the problem. The level of detail included in a model thus depends on the problem to be solved-as well as on the problem solver. Based on such an idealised picture, the system is described in a suitable form that is used as a basis for deriving a solution (Fig. 1.1). After obtaining a solution, results are interpreted with respect to the real-world context of the original system. Thus, as well as being able to create a valid model of the system, and to solve it, it is of great importance to represent the solution in a form that can be understood readily and communicated. The traditional modelling approach used in engineering is mathematical. That is, real-world physical processes are described by mathematical relationships that are solved using suitable analytical or numerical techniques. As real engineering systems are very complex, it is not an easy task to create a valid model and solve it. An added practical consideration is that problems must be solvable efficiently in terms of resources and time. Advances in computer technology have dramati-
cally improved solvability; it is now possible to solve problems that formerly were intractable. Solving problems with a computer means that a problem posed in one physical domain is solved in another physical domain, the computer domain. This naturally leads to the topic of simulation modelling. Simulation models mimic the behaviour of engineering processes in their environment. By experimenting on models of equipment instead of on real equipment, the system's behaviour can be studied even before the hardware is built. Simulation models can be used at various stages of design, from the early stages of conceptual design to final prototype testing. There are many fields in which this technique has been applied profitably. The fundamental question that naturally arises is: How are such models best constructed? A well-known adage suggests that modelling is more art than science. It is, in fact, a bit of both. On the "scientific" side, there are a number of approaches, methods, and tools that can be mastered, and then applied, to develop effective models; the "art", perhaps, is the insight that a modeller accumulates through practice and familiarity with the system being studied. V. Dami et al., Mechatronics by Bond Graphs © Springer-Verlag Berlin Heidelberg 2003
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1 Basic Forms of Model Representation Abstraction
Fig. 1.1. Model approach to problem solution
This chapter reviews some of the more promising approaches and methods at the foundation of modelling. The perspective adopted is motivated mainly by problems in mechatronics. There are many definitions of mechatronics. lOne that we choose to highlight states that mechatronics is a synergi
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