User`s guide

3 Linear Model Identification
smallest contribution. Based on this plot, select the rectangle that represents
the cutoff for the states on the left that provide a significant contribution to
the input-output behavior. The recommended choice is red.
For e xample, in the previous figure, states 1 and 2 provide the most significant
contribution. However, the contributions of the states to the right of state 2
drop significantly. This sharp decrease in the log of the singular values after
n=2 indicates that using two states is sufficient to get an accurate model.
How to Estimate State-Space M odels in the GUI
• “Supported State-Space Models in the GUI” on page 3-84
• “Before You Be gin” on page 3-84
• “Estimating State-S pa ce Models in the GUI” on page 3-84
Supported State-Space Models in the GUI
Only free parameterization is directly supported in the System Identification
Tool GUI. You can also estimate canonical and structured parameterizations
at the com mand line and import them into the System Identification Tool
GUI for p arameter estimation. For more information about state-space
parameterization, see “Supported State-Space Parameterizations” on page
3-78.
Before You Begin
Before you estimate state-space models, you must have already imported your
data into the GUI and performed any necessary preprocessing operations. For
more information, see Chapter 1, “Data Processing”.
The following pro cedure also requires that you specify model order and
input delays. For more information about how to estimate model orders, see
“Estimating Model O rder in the GUI” on page 3-79.
Estimating State-Space Models in the GUI
To estimate a state-space model with free parameterization in the System
Identification Tool GUI:
3-84