MATLAB: Parameter optimization without real input-output model

Question

Hello,

I'm building a model of an accelerating engine in SimuLink, and based on real logged data I want to approximate my parameters (Cd, rolling coefficient) such that they reflect reality. To achieve this I'm using the Control and Estimation Tools manager. I think is a suitable tool but I have some problems with the implementation. The examples I've found on internet all concern an input-output based situation, such a DC engine. However, the nature of my model is a bit different. I just supply initial conditions (entry speed, gear etc.) to run the simulation. As such, I do not have a clear input-output model that i can specify for the optimizer, and thus the parameter optimizer says that the object function is in a local minimum.

I hope it's a bit clear what I mean, and you can help me out 🙂

Answer 1

As I understand the optimization problem, you would like to minimize something at the end of the day (like least square error between an experimental and model time domain data). Keeping that in mind, I suppose you have some real world (or experimental) data. What kind of data is that? I suppose that should be some time domain vectors (input and output, or, as far as you're refering to some non-I\O case, just output by constant input).

I would say you have to repeat the same situation you have in real world in your model and ask Parameter Estimator to tune the parameters.