You can perform horizontal and vertical concatenation of linear model objects to grow the number of inputs or outputs in the model.
When you concatenate identified models, such as
idss model objects, the resulting model combines
the parameters of the individual models. However, the estimated parameter
covariance is lost. If you want to translate the covariance information
during concatenation, use
Concatenation is not supported for
convert them to
idss models first if you want
to perform concatenation.
You can also concatenate nonparametric models, which contain
the estimated impulse-response (
and frequency-response (
idfrd object) of a system.
In case of
idfrd models, concatenation
combines information in the
of the individual model objects.
that stores the response of the system, where
the number of output channels,
nu is the number
of input channels, and
nf is the number of frequency
(j,i,:) vector of the resulting response
data represents the frequency response from the
input to the
jth output at all frequencies.
Concatenation is supported for linear models only.
Horizontal concatenation of model objects requires that they have the same outputs. If the output channel names are different and their dimensions are the same, the concatenation operation resets the output names to their default values.
The following syntax creates a new model
m that contains the horizontal concatenation
m = [m1,m2,...,mN]
all of the inputs of
m1,m2,...,mN to the same outputs
as in the original models. The following diagram is a graphical representation
of horizontal concatenation of the models.
Vertical concatenation combines output channels of specified
models. Vertical concatenation of model objects requires that they
have the same inputs. If the input channel names are different and
their dimensions are the same, the concatenation operation resets
the input channel names to their default (
The following syntax creates a new model object
contains the vertical concatenation of
m = [m1;m2;... ;mN]
the same inputs in the original models to all of the output of
The following diagram is a graphical representation of vertical concatenation
of frequency-response data.
idfrd models are obtained as a result
of estimation (such as using
is not empty and contains the power spectra and cross spectra of the
output noise in the system. For each output channel, this toolbox
estimates one noise channel to explain the difference between the
output of the model and the measured output.
SpectrumData property of individual
is not empty, horizontal and vertical concatenation handle
In case of horizontal concatenation, there is no meaningful
way to combine the
SpectrumData of individual
and the resulting
SpectrumData property is empty.
An empty property results because each
has its own set of noise channels, where the number of noise channels
equals the number of outputs. When the resulting
contains the same output channels as each of the individual
it cannot accommodate the noise data from all the
In case of vertical concatenation, this toolbox
concatenates individual noise models diagonally. The following shows
m.SpectrumData is a block diagonal matrix
of the power spectra and cross spectra of the output noise in the
the abbreviation for the
If you have the Control System Toolbox™ product, see Combining Model Objects about additional functionality for combining models.