estimation experiment is typically much faster with a superposition signal with
satisfactory results.
To specify which type of input signal to use for online estimation, use the Experiment
mode parameter of the Frequency Response Estimator block.
Sinestream Signals
For details about the structure of sinestream signals and how to create them, see
“Sinestream Input Signals” on page 5-37.
Chirp Signals
For details about the structure of chirp signals and how to create them, see “Chirp Input
Signals” on page 5-42.
Random Signals
Random signals are useful because they can excite the system uniformly at all
frequencies up to the Nyquist frequency. To create a random input signal for estimation:
- In the Linear Analysis Tool, in the Estimation tab, select Input Signal > Random.
- At the command line, use frest.Random to create the random signal and use it as an
input argument to frestimate.
The random signal comprises uniformly distributed random numbers in the interval [0
Ampltidue] or [Amplitude 0] for positive and negative amplitudes, respectively. You
can specify the amplitude, sample time, and number of samples directly when you create
the input signal. Alternatively, if you have a relevant linear time-invariant (LTI) model
such as a state-space (ss) model, you can use it to initialize the random signal
parameters. For instance, if you have an exact linearization of your system, you can use it
to initialize the parameters.
When you use a random input signal for estimation, the frequencies returned in the
estimated frd model depend on the length and sampling time of the signal. They are the
frequencies obtained in the fast Fourier transform of the input signal (see the Algorithm
section of frestimate).
Estimation Input Signals