|System Identification||Identify models of dynamic systems from measured data|
|Estimate impulse response using prewhitened-based correlation analysis|
|Nonparametric impulse response estimation|
|Obtain model parameters and associated uncertainty data|
|Modify values of model parameters|
|Options set for |
Estimate in the app using time-domain correlation analysis.
impulseest command to estimate
using correlation analysis.
Obtain numerical impulse- and step-response vectors as a function of time.
You can use transient-response plots to estimate the input delay, or dead time, of linear systems. Input delay represents the time it takes for the output to respond to the input.
Time-domain correlation analysis refers
to non-parametric estimation of the impulse response of dynamic systems
as a finite impulse response (FIR) model from the data. The estimated
model is stored as transfer function model object (
idtf). For information about transfer
function models, see What are Transfer Function Models?.
Characteristics of data supported for estimation of impulse-response models.
Correlation analysis refers to methods that estimate the impulse response of a linear model, without specific assumptions about model orders.