Acausal models Sample Clauses

Acausal models. An acausal model is a model where the behaviour is represented as equations, or constraints. The word acausal could be misleading, since it is a negative definition (i.e. models not being causal). An acausal model should rather be seen as a set of equations, or constraints. Constraints can have a specified cause and effect, for example: y = if v > limit then limit else v; Although labeled as an acausal model, there is a causality where a value of v gives a value of y. The following model is of a bouncing ball: der(height) = velocity; der(velocity) =-g; when height <= radius then reinit(velocity, -c*pre(velocity)); The model is acausal in the sense that either of the variables height, velocity or g could be used as input to the model. Another way of expressing this is that the number of equations vs the number of unknowns have to be matched. Acausal models are often associated with the Modelica language. Modelica combines acausal modelling with object-oriented thinking. For interfaces between physical components, it is favorable to use acausal modelling, together with power port connectors where effort and flow information is interchanged. This way, physical components can be connected to each other, similar to how they are connected physically. Another advantage of using this realization level is that equations can be simplified and even solved analytically. Two new tools were released this year: Simscape 3.0 from the MathWorks, and MapleSim from Maplesoft. Both these tools are similar to Modelica: combining equation based effort/flow modelling, which enables physical modelling. Also SystemC-AMS and VHDL-AMS uses acausal models, but limited to electric systems.
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