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System Identification | Identify models of dynamic systems from measured data |
cra | Estimate impulse response using prewhitened-based correlation analysis |
impulseest | Nonparametric impulse response estimation |
getpvec | Obtain model parameters and associated uncertainty data |
setpvec | Modify values of model parameters |
impulseestOptions | Options set for impulseest |
Estimate Impulse-Response Models Using System Identification App
Estimate in the app using time-domain correlation analysis.
Estimate Impulse-Response Models at the Command Line
Use impulseest
command to estimate
using correlation analysis.
Obtain numerical impulse- and step-response vectors as a function of time.
Identify Delay Using Transient-Response Plots
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.
What Is Time-Domain Correlation Analysis?
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?.
Data Supported by Correlation Analysis
Characteristics of data supported for estimation of impulse-response models.
Correlation Analysis Algorithm
Correlation analysis refers to methods that estimate the impulse response of a linear model, without specific assumptions about model orders.