User`s guide

3 Linear Model Identification
For frequency-domain data, no noise model is estimated and K is set to 0. For
time-domain data, K is estimated by default.
To modify whether K is estimated for time-domain d ata, you can specify the
DisturbanceModel property in the estimator sy ntax.
Initially, you can omit estimating the noise parameters in K to focus on
achieving a reasonable model for the system dynamics. After estimating the
dynamic model, you can use
pem to refine the model and set the K parameters
to be estimated. For example:
m = pem(Data,md,'DisturbanceModel','Estimate')
where md is the dynamic model without noise.
To set K to zero, set the value of the
DisturbanceModel property to 'None'.
For example:
m = pem(Data,n,'DisturbanceModel','None')
XO Matrices. X0 stores the estimated or specifie d initial states of the mo del.
To specify how to handle the initial states, set the value of the
InitialStates
model property. For example, to set the initial states to zero, set the
InitialStates property to 'zero',asfollows:
m = pem(Data,n,'InitialStates','zero')
When you estimate models using multiexperime nt data and InitialSta tes
is set to 'Estimate', X0 stores the estimated initial states corresponding to
the last experiment in the data set.
For a comp lete list of va lues for the
InitialStates property, see “Options for
Initial States” on page 3-101.
How to Estimate Free-Parameterization State-Space
Models
The default parameterization of the state-space matrices A, B, C , D,andK is
free; that is, any elements in the matrices are adjustable by the estimation
3-90