Documentation |
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 idfrd model. If you have the Control System Toolbox™ product, this command converts any numeric LTI model too. | To get frequency response of m at default
frequencies, use the following command: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 2 to output 3, use the following command: m_f = idfrd(m(2,3)) |
idpoly | Converts any linear identified model, except idfrd,
to ARMAX representation if the original model has a nontrivial noise
component, or OE if the noise model is trivial (H =
1). If you have the Control System Toolbox product, this command converts any numeric LTI model, except frd. | To get an ARMAX model from state-space model m_ss,
use the following command:m_p = idpoly(m_ss) |
idss | Converts any linear identified model, except idfrd,
to state-space representation. If you have the Control System Toolbox product, this command converts any numeric LTI model, except frd. | To get a state-space model from an ARX model m_arx,
use the following command:m_ss = idss(m_arx) |
idtf | Converts any linear identified model, except idfrd,
to transfer function representation. The noise component of the original
model is lost since an idtf object has no elements
to model noise dynamics. If you have the Control System Toolbox product, this command converts any numeric LTI model, except frd. | To get a transfer function from a state-space model m_ss,
use the following command: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:
If you want to translate the estimated parameter covariance during conversion, use translatecov. |