User`s guide

3 Linear Model Identification
How to Estimate the State-Space Equivalent of
ARMAX and OE Models
You can estimate the equivalent of ARMA X and output-error (OE )
multiple-output models using state-space model structures. For the ARMAX
case, specify to estimate the K matrix for the state-space model. For the OE
case, set K to z ero.
For more information about ARMAX and OE models, see “Identifying
Input-Output Polynomial Models” on page 3-41.
Options for Frequency-Weighing Focus
You can specify how the estimation algorithm weighs the fitatvarious
frequencies. This information supports the estimation procedures “How to
Estimate State-Space Models in the GUI” on page 3-84 and “How to Estimate
State-Space Models at the C ommand Line ” on page 3-87.
In the System Identifi cation Tool GUI. Set Focus to one of t he following
options:
•
Prediction — Uses the inverse of the noise model H to weigh the relative
importance of how closely to fit the data in various frequency ranges.
Corresponds to minimizing one-step-ahead prediction, which typically
favors the fit over a short time interval. O ptimized for output prediction
applications.
•
Simulation — Uses the input spectrum to weigh the relative importance of
the fitinaspecific frequency range. Does not use the noise model to w eigh
the relative importance of how closely to fit the data in various frequency
ranges. Optimized for output simulation applications.
•
Stability — Estimates the best stable model. For more information about
model stability, see “Unstable Models” on page 8-69.
•
Filter —Specifyacustomfilter to open the Estimation Focus dialog box,
where you can enter a filter, as described in “Simple Passband Filter” on
page 1-111 or “Defining a Custom Filter” on page 1-112. This prefiltering
applies only for estimating the d ynamics from input to output. The
disturbance model is determ ined from the estimation data.
3-100