Uncertainty Analysis
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.
Funzioni
present | Display model information, including estimated uncertainty |
simsd | Simulate linear models with uncertainty using Monte Carlo method |
freqresp | Evaluate system response over a grid of frequencies |
rsample | Random sampling of linear identified systems |
showConfidence | Display confidence regions on response plots for identified models |
getcov | Parameter covariance of identified model |
setcov | Set parameter covariance data in identified model |
translatecov | Translate parameter covariance across model transformation operations |
step | Step response of dynamic system |
stepplot | Plot step response of dynamic system |
impulse | Impulse response plot of dynamic system; impulse response data |
bode | Bode frequency response of dynamic system |
bodemag | Magnitude-only Bode plot of frequency response |
nyquist | Nyquist response of dynamic system |
nyquistplot | Plot Nyquist response of dynamic system |
iopzmap | Plot pole-zero map for input-output pairs of dynamic system using default options |
iopzplot | Plot pole-zero map for input-output pairs of dynamic system |
simsdOptions | Option set for simsd |
Esempi e istruzioni
- 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.
Concetti
- Compute Model Uncertainty
Compute model parameter uncertainty of linear models.