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The purpose of this toolbox is to find the parameters of a system by comparing experiments and models together where the parameters are considered unknowns. If the same inputs are applied to the experiments and models there will be a solution (or several) that will minimize the difference between models and experiments. After a solution is found you can then use this parameters to estimate what will happen in situations where you donít have the actual data.

You will use a tool called Parameter Optimizer to solve this problem. With this tool you will specify all the properties of the problem needed such as: models to be used, experimental curves, variables to compare, parameters to estimate, etc. The way to create models in Pspice and Simulink for this tool and a general explanation of the problem can be found in the model creation section. If youíre curious you can also read about how the algorithm works and read some tips at the end. The tool has a wizard to help you specify all this information easily trough a GUI. It also comes with a tool called Data Picker to transform image graphs to points.

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