tf - Convert linear models to transfer-function Control System Toolbox LTI models

Syntax

sys = tf(mod)
sys = tf(mod,'m')

Description

mod is any idmodel object: idgrey, idarx, idpoly, idproc, idss, or idmodel.

sys is returned as a transfer function tf LTI model object. The noise input channels in mod are treated as follows:

Consider a model mod with both measured input channels u (nu channels) and noise channels e (ny channels) with covariance matrix

where L is a lower triangular matrix. mod.NoiseVariance = . The model can also be described with a unit variance, using a normalized noise source v.

Both measured input channels u and normalized noise input channels v in mod are input channels in sys. The noise input channels belong to the InputGroup 'Noise', while the others belong to the InputGroup 'Measured'. The names of the noise input channels will be v@yname, where yname is the name of the corresponding output channel. This means that the LTI object realizes the transfer function [G HL].

To transform only the measured input channels in mod, use

sys = tf(mod('m')) or sys = tf(mod,'m')

This gives a representation of G only.

For a time series, (no measured input channels, nu = 0), the LTI representation contains the transfer functions from the normalized noise sources v to the outputs, that is, HL. If the model mod has both measured and noise inputs, sys = tf(mod('n')) gives a representation of the additive noise.

In addition, you can use normal subreferencing.

sys = tf(mod(1,[3 4]))

If you want to describe [G H] or H (unnormalized noise), from e to y, first use

mod = noisecnv(mod)

to convert the noise channels e to regular input channels. These channels are assigned the names e@yname.

tf - Convert linear models to transfer-function Control System Toolbox LTI models

Syntax

Description

See Also

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