You can transform linear models between state-space and polynomial forms. You can also transform between frequency-response, state-space, and polynomial forms.
If you used the System Identification app to estimate models, you must export the models to the MATLAB® workspace before converting models.
For detailed information about each command in the following table, see the corresponding reference page.
Commands for Transforming Model Representations
| Command | Model Type to Convert | Usage Example |
|---|---|---|
idfrd |
Converts any linear model to an If you have the Control System Toolbox™ product, this command converts any numeric LTI model too. |
To get frequency response of m_f = idfrd(m) To get frequency response at specific frequencies, use the following command: m_f = idfrd(m,f) To get frequency response for a submodel from input
m_f = idfrd(m(2,3)) |
idpoly |
Converts any linear identified model, except
If you have the Control System Toolbox product, this command converts any numeric LTI
model, except |
To get an ARMAX model from state-space model
m_p = idpoly(m_ss) |
idss |
Converts any linear identified model, except
If you have the Control System Toolbox product, this command converts any numeric LTI
model, except |
To get a state-space model from an ARX model
m_ss = idss(m_arx) |
idtf |
Converts any linear identified model, except
If you have the Control System Toolbox product, this command converts any numeric LTI
model, except |
To get a transfer function from a state-space model
m_tf = idtf(m_ss) |
Note
Most transformations among identified models (among idss, idtf, idpoly)
causes the parameter covariance information to be lost, with few exceptions:
Conversion of an idtf model to
an idpoly model.
Conversion of an idgrey model
to an idss model.
If you want to translate the estimated parameter covariance
during conversion, use translatecov.