User`s guide

Identifying Input-Output Polynomial Models
• Single-output and multiple-output.
You m us t import your data into the MA TLAB workspace , as described in
Chapter 1, “Data Processing”.
Designating Data for Estimating Continuous-Time Models
To get a linear, continuous-time model of arbitrary structure for tim e-do m ain
data, y ou can estimate a discrete-time model, and then use
d2c to transform
it to a continuous-time model.
For continuous-time frequency-domain data, you can estimate directly only
the ARX and Output-Error (OE) continuous-time models. Other structures
include noise m odels, which is not supported for frequency-domain data.
Tip To denote continuous-time frequency-domain data, set the data sampling
interval to 0. You can set the sampling interval when you import data into
the GUI or set the
Ts property of the data object at the command line.
Designating Data for Estimating Discrete-Time Models
You can estimate arbitrar y-ord er, linear state-space models for both time- or
frequency-domain data.
Your data must have the data property
Ts set to the experimental data
sampling interval.
Tip You can set the sampling interval when you import data into the GUI or
set the
Ts property of the data object at the command line.
Preliminary S tep – E stimating Model Orders and
Input Delays
• “Why Estimate Model Orders and Delays?” on page 3-50
• “Estima t in g Orders and Del ay s in the GUI” on page 3-50
3-49