User`s guide

3 Linear Model Identification
This approach differs from estimating models with free and canonical
parameterizations, where it is not necessary to specify initial parameter
values before the estimation. For free parameterization, there is no
structure to specify because it is assumed to be unknown. For canonical
parameterization, the structure is fixed to a specificform.
For information about validating your model, see “Overview of Model
Validation and Plots” on page 8-2.
Specifying the State-Space Structure
To s pecify the state-space m odel structure, first define the A, B, C, D, K and X0
matrices in the MATLAB workspace.
To define a discrete-time state-space structure, use the following syntax:
m = idss(A,B,C,D,K,X0,...
'Ts',T,...
'SSparameterization','structured')
where A, B, C, D,andK spec ify b oth the fixed parameter values and the
initial values for the free parameters.
T is the sampling in t erval. Setti ng
SSparameterization to 'structure d' fl ags that you want to estimate a
partial structure for this state-space model.
Similarly, to define a continuous-time state-space structure, use the following
syntax:
m = idss(A,B,C,D,K,X0,...
'Ts',0,...
'SSparameterization','structured')
In the continuous-time case, you must set the sampling interval property Ts
to zero.
After you create the nominal model structure, you must specify which
parameters to estimate and which to set to specific values. To accomplish this,
you m us t edit the structures of the following model properties:
As, Bs, Cs, Ds,
Ks,andx0s.Thesestructure matrices are p roperties of the nominal model
you constructed and have the same sizes as
A, B, C, D, K,andx0,respectively.
Initially, the structure matrices contain
NaN values.
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