User`s guide

Identifying Input-Output Polynomial Models
After estimating model orders and d elay s, use these values as initial guesses
for estimating other model structures, as described in “Using pem to Estimate
Polynomial Models” on page 3-61.
Estimating Delays at the Command Line
The delayest command estimates the time delay in a dynamic system by
estimating a low-order, discrete-time ARX model and treating the d elay as an
unknown parameter.
By default,
delayest assumes that n
a
=n
b
=2 and that there is a good
signal-to-noise ratio, and uses this information to estimate n
k
.
To estimate the delay for a data set
data, type the foll owing at the prom pt:
delayest(data)
If your data has a single input, MA TLAB computes a scalar value for the
input delay—equal to the number of data samples. If your data has multiple
inputs, MATLAB returns a vector, where each value is the delay for the
corresponding input signal.
To compute the actual delay time, you must multiply the input delay by the
sampling interval of the data.
You can also use the ARX Model Structure Selection window to estimate input
delays and model order together, as described in “Estimating M odel Orders at
the Comm and Line” on page 3-53.
SelectingModelOrdersfromtheBestARXStructure
You gen erate the A RX Model Structure Selection window for your data to
select the best-fit model.
For a procedure on generating this plot in the System Ide ntification Tool GUI,
see “Estimating Orders and Delays in the GUI” on page 3-50. To open this
plot at th e command line, see “Estimating Model Orders at the Command
Line” on page 3-53.
The following figure shows a sample plot in the AR X Model Structure
Selection w indow.
3-55