System Identification Toolbox | ![]() ![]() |
Model Error Models
returns the iddata
object e
which has the inputs in Data
as inputs and the prediction errors (residuals) as outputs. Building models using e
will thus reveal if there is any significant influence from u
to e
left in the data. Such models are called Model Error Models, and examining them is a good complement to traditional residual analysis.
E= resid(Model,Data) impulse(E,'sd',3) % An alternative to residual analysis bode(spa(E),'sd',3) % Shows the frequency ranges % with significant model errors m = arx(E,[0 10 0]) bode(m,'sd',3)
Note that the resid
command has several options to display model error properties rather than correlation functions.
![]() | Residual Analysis | Noise-Free Simulations | ![]() |