Transforming Between Linear Model Representations
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 anidpoly
model.Conversion of an
idgrey
model to anidss
model.
If you want to translate the estimated parameter covariance
during conversion, use translatecov
.