User`s guide

Identifying State-Space Models
At the command line. Specifythefocusasanargumentinthe
model-estimation command using the same options as in the GUI. For
example, use this command to emphasize the fit betwe en the 5 and 8 rad/s:
pem(data,4,'Focus',[5 8])
Options for Initial States
If you estimate state-space models using the iterative estimation algorithm
pem, you must specify how the algorithm treats initia l states. This inform a t ion
supports the estimation procedures “How to Estimate State-Space Models
in the GUI” on page 3-84 and “How to Estimate State-Space Models at the
Command Line” on page 3-87.
In the System Identification Tool GUI. Set Initial state to one o f the
following o ptions:
•
Auto — Autom atically chooses Zero, E stim ate,orBackcast based on the
estimation data. If initial states hav e negligible effect on the prediction
errors, the initial states are set to zero to optimize algorithm performance.
•
Zero — S ets all initia l states to zero.
•
Estimate — Treats the initial states as an unknown vector of param eters
and estimates these states from the da ta.
•
Backcast — E stimates in itial sta tes using a backward filtering method
(least-squares fit).
At the command line. Specify the initial states as an argument in the
estimation comm and
pem. For example, use this command to estimate a
fourth-order state-space model and set the initial states to be estimated from
the data:
m=pem(data,4,'InitialState','estimate ')
For a complete list of valu es for t he InitialSt ate model property, see the
idss reference page.
Algorithms for Estimating State-Space Models
For linear state-space models, you canusethesubspacemethod,called
N4SID. You can use the subspace method N4SID to get an i nitial model (see
3-101