Does the accuracy of system identification affect performance of controlling an object in control engineering?
For example, I did system identification and obtained matrix A, B, C, D using method A and the cross correlation with the actually measured data is 0.6.
And we did the same thing with method B and we have got the cross correction 0.8.
In this case, we can say that for system identification, method B is better than method A.
Usually in this case, can we get a better control performance result using the A, B, C, D matrix from method B compared with A?
Indeed, Good accuracy of the system means, the system is controllable, observable, .... good convergence.... equilibrium ...more useful .... no or very low singularities or outlairs....etc.
The accuracy of the model has a direct impact to the performance of the controller. However, you want to void over-fitting your model to your training data. Avoid choosing a high order model to exactly match your data.
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