User`s guide

2 Choosing Your System Identification Strategy
data, you can estimate continuous-tim e black-box models with canonical
parameterization. See “Identify ing State-Space Models” on page 3-73.
To get a linear, continuous-time model of arbitrary structure for
frequency-domain data, you can est imate a discrete-time model and use
d2c
to transform it to a continuous-time model.
Discrete-Time Models
You can estimate only ARX and output-error ( O E) polynomial models using
frequency-domain data. See “Identifying Input-Output Polynomial Mo dels”
on page 3-41.
Other linear model structures include noise models, which are not supported
for frequency-domain data.
ODEs (Grey-Box Models)
For linear grey-box m odels , you can estimate both continuous-time and
discrete-time models from frequency-domain data.
Nonlinear grey-box models are supported only for time-domain data.
See Chapter 5, “ODE Parameter Estimation (Grey-Box Modeling)”.
Nonlinear Black-Box Models
Frequency-domain data is no t releva nt to nonlinear black-box models, w h ich
support only time-domain data.
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