Products & Services Solutions Academia Support User Community Company

Learn more about System Identification Toolbox   

Extracting Dynamic Model and Noise Model Separately

You can extract the numerical data associated with a dynamic model and the noise model separately.

For linear models, the general symbolic model description is given by:

G is an operator that takes the measured inputs u to the outputs and captures the system dynamics. H is an operator that describes the properties of the additive output disturbance and takes the hypothetical (unmeasured) noise source inputs e to the outputs, also called the noise model. When you estimate a noise model, the toolbox includes one noise channel e at the input for each output in your system.

The following table summarizes the results of ssdata, tfdata, and zpkdata commands for extracting the numerical values of the dynamic model and noise model separately. fcn represents ssdata, tfdata, and zpkdata, and m is a model object. L represents the covariance matrix e, as defined in Subreferencing Measured and Noise Models.

For information about subreferencing noise channels or treating noise channels as measured input, see Subreferencing Model Objects.

Syntax for Extracting Transfer-Function Data

CommandSyntax
fcn(m)Returns the properties of G for ny outputs and nu inputs.
fcn(m('noise'))Returns the properties of H for ny outputs and ny inputs.
fcn(noisecnv(m))Returns the properties of [GH] ny outputs and ny+nu inputs.
fcn(noisecnv(m,'Norm'))Returns the properties of [GHL] ny outputs and ny+nu inputs.
fcn(noisecnv(m('noise'),'Norm'))Returns the properties of HLny outputs and ny inputs.
fcn(m)If m is a time-series model, returns the properties of H.
fcn(noisecnv(m,'Norm'))If m is a time-series model, returns the properties of HL.

  


Recommended Products

Includes the most popular MATLAB recorded presentations with Q&A sessions led by MATLAB experts.

 © 1984-2009- The MathWorks, Inc.    -   Site Help   -   Patents   -   Trademarks   -   Privacy Policy   -   Preventing Piracy   -   RSS