Hello,
what I want: I will determine the process parameters of a first order system (maybe also 2nd order).
The problem: I have not the "space" to get the parametes of an long testrun, because there are contraints at the machine of available turns from start to end.
My idea:
- I give a arbitrary signal to the process input. I think its important to have significant high frequencies to get an output to determine the system. It would not be able to get the systemparameters, if I only input a constant to the process.
- I will sample the input and output of the real process for an "adequate" time
- determining the Process parameters: If I know that the process is a first order type (G(s) = K/(1+s*T), I take the formula of the time- domain which describes the relation of the input and output of an first order system. The Parameters are K and T.
- Then I will give the real sampled input and calculate the output by my model, which is a function of K and T.
- Then I will make a benching of the output, e.g. by summation of the square-difference of the real output and the modelled output. As higher the integral summation as more deviation is betwen the real parameters and the model parameters.
- then I will vary K and T and make a new summation of the aquare difference.
- Finally I will take the K and T where the least summation value occurs.
As extension I can also put the input at a second order model. If the square-error-summation has a lower value as the first order type, then I will use the 2nd oder Modell and Parameters for modelling the real process.
How do you think about it?
Wolfgang