User`s guide

3 Linear Model Identification
To omit estimating uncertainty, select None. Skipping uncertainty
computation might reduce computation tim e for complex models and large
data sets.
10 In the Model Name field, edit the name of the model or keep the default.
The name of the model should be unique in the Model Board.
11 To view the estimation progress in the MATLAB Command Window, select
the Trace check box. During estimation, the fo llowing informa t ion is
displayed for each iteration:
• Loss function — Equals the determinant of the estimated covariance
matrix of the input noise.
• Parameter values — Values of the model structure coefficients you
specified.
• Search direction — Change in parameter values from the previous
iteration.
• Fit improvements — Shows the actual versus e xpected impro vem ents in
the fit.
12 Click Estima te to add this model to the Model B oard in the System
Identification Tool GUI.
13 To stop the search and save the results after the current iteration has been
completed, click Stop Iterations. To conti nue iterations from the current
model, click the Continue iter button to assign current parameter values
as initial guesses for the next search.
14 To plot the model, select the appropriate check box i n the Model Views
area of the System Identification Tool G U I. For m ore information about
validating models, see “Overview o f Model Validation and P lots” on page
8-2.
15 To refine the current estimate, click the Value —> Initial Guess button
to assign current parameter values as initial gues ses for the next search,
edit the Model Name field, and click Estimate.
If your model is not sufficiently accurate, try another model structure.
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