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Uncertainty Analysis

Compute parameter variability, plot confidence bounds

When you estimate the model parameters from data, you obtain their nominal values that are accurate within a confidence region. The size of this region is determined by the values of the parameter uncertainties computed during estimation. The magnitude of the uncertainties provide a measure of the reliability of the model. You can compute and visualize the effect of parameter uncertainties on the model response in time and frequency domains.

Functions

presentDisplay model information, including estimated uncertainty
simsdSimulate linear models with uncertainty using Monte Carlo method
freqrespFrequency response over grid
rsampleRandom sampling of linear identified systems
showConfidenceDisplay confidence regions on response plots for identified models
getcovParameter covariance of identified model
setcovSet parameter covariance data in identified model
translatecovTranslate parameter covariance across model transformation operations
stepStep response plot of dynamic system; step response data
stepplotPlot step response and return plot handle
impulseImpulse response plot of dynamic system; impulse response data
bodeBode plot of frequency response, or magnitude and phase data
bodemagBode magnitude response of LTI models
nyquistNyquist plot of frequency response
nyquistplotNyquist plot with additional plot customization options
iopzmapPlot pole-zero map for I/O pairs of model
iopzplotPlot pole-zero map for I/O pairs and return plot handle
tfdataAccess transfer function data
zpkdataAccess zero-pole-gain data
simsdOptionsOption set for simsd

Examples and How To

Plot Impulse and Step Response Using the System Identification App

To create a transient analysis plot in the System Identification app, select the Transient resp check box in the Model Views area.

Plot Bode Plots Using the System Identification App

To create a frequency-response plot for linear models in the System Identification app, select the Frequency resp check box in the Model Views area.

Plot the Noise Spectrum Using the System Identification App

To create a noise spectrum plot for parametric linear models in the app, select the Noise spectrum check box in the Model Views area.

Plot the Noise Spectrum at the Command Line

To plot the disturbance spectrum of an input-output model or the output spectrum of a time series model, use spectrum.

Model Poles and Zeros Using the System Identification App

To create a pole-zero plot for parametric linear models in the System Identification app, select the Zeros and poles check box in the Model Views area.

Concepts

Computing Model Uncertainty

Computing model parameter uncertainty of linear models.

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