System Identification Toolbox

Step 1: Looking at the Data

Plot the data. Look at them carefully. Try to see the dynamics with your own eyes. Can you see the effects in the outputs of the changes in the input? Can you see nonlinear effects, like different responses at different levels, or different responses to a step up and a step down? Are there portions of the data that appear to be "messy" or carry no information. Use this insight to select portions of the data for estimation and validation purposes.

Do physical levels play a role in your model? If not, detrend the data by removing their mean values. The models will then describe how changes in the input give changes in output, but not explain the actual levels of the signals. This is the normal situation.

The default situation, with good data, is that you detrend by removing means, and then select the first half or so of the data record for estimation purposes, and use the remaining data for validation. This is what happens when you apply Quickstart under the pop-up menu Preprocess in the main ident window.

A Startup Identification Procedure

Step 2: Getting a Feel for the Difficulties