System Identification Toolbox

Comparing Different Models

It is a good idea to display the model properties in terms of quantities that have more physical meaning than the parameters themselves. Bode plots, pole-zero plots, and model simulations all give a sense of the properties of the system that have been picked up by the model.

If several models of different characters give very similar Bode plots in the frequency range of interest, you can be fairly confident that these must reflect features of the true, unknown system. You can then choose the simplest model among these.

A typical identification session includes estimation in several different structures, and comparisons of the model properties. Here is an example.

• a1 = arx(Data,[1 2 1]);
  g = spa(Data);
  bode(g,a1)
  bode(g('n'),a1('n'))% the output disturbance spectra
  am2 = armax(Data,[2 2 2 1]);
  bode(g,am2)
  pzmap(a1,am2,'sd',3)
  

Assessing the Model Uncertainty

Selecting Model Structures for Multivariable Systems