Importing and Preprocessing Experiment Data (GUI)

RC Circuit Model

The Simulink® model,sdoRCCircuit, models a simple resistor-capacitor (RC) circuit.

open_system('sdoRCCircuit');

You use measured data to estimate the RC model parameter and state values.

Measured output data:

Parameter:

State:

Define the Estimation Experiment

In this example, you load the measured data from a saved MATLAB® file. The data is also stored in a comma separated variable (csv) text file. You can also load the measured data directly from text or Excel® files.

First load the measured data from the MATLAB file, the file defines two variables,timeanddatathat specify the measured capacitor voltage.

loadsdoRCCircuit_ExperimentData

To launch theParameter Estimator, in the Simulink model window, in theAppsgallery, underControl Systems, clickParameter Estimator.

ClickNew Experimentto create an estimation experiment that contains the measured data. A variableExpis created in theParameter Estimatorand a dialog to edit the experiment opens.

实验编辑器包含部分指定measured output data and sections to optionally specify experiment initial states and parameters.

The experiment editor automatically adds measured output signals for model root level ports and logged model signals. ClickSelect Signalsto add additional measured outputs if needed. For this example the capacitor voltage signal is logged in the model and already added to the experiment.

Specify the measured capacitor voltage by typing[time data]in the edit field. This uses the MATLAB variablestimeanddataloaded from file earlier to specify the measured capacitor voltage. Measured data is specified as a matrix where the 1st column is time and subsequent columns signal data.

Alternatively, you can specify the measured capacitor voltage variables by loading the measured data directly from text or Excel files. Click the import button to open a file browser and selectsdoRCCircuit_ExperimentData.csvfile.

A tool for importing column data from a file opens. The first column selected for import is used to specify the signal time, subsequent columns selected for import are used to specify the signal data. Select thetimeanddatacolumns and clickImport Selection.

In the experiment editor clickPlot & Simulateto plot the measured experiment data and the simulated model response.

The experiment plot shows that the simulated data does not match the measured data. The plot also shows that the model initial state is not correct and needs to be estimated (the measured and simulated voltages at time 0 are significantly different). From the experiment editor, clickSelect Initial Statesto open a dialog to select model initial states; select thesdoRCCircuit.C1.vcstate and clickOkto add the state to the experiment.

Preprocess the Experiment Data

The measured data contains high frequency noise that you can remove using a low-pass filter. Click theExperiment Plottab and selectLow Pass Filter.

This opens the Low-Pass Filter tool. The upper axis shows the signal FFT, the lower axis shows the signals. The original signal is shown in blue and the filtered signal in red. Adjust the filter bandwidth by either typing a value in theNormalized cutoff frequencyedit field or clicking and dragging the yellow patch edge. Drag the filter cutoff to 0.4. ClickOptionsand selectZero-phase shift filterto avoid introducing the filter phase shift into the measured data.

ClickApplyandClose Low-Pass Filterto complete low-pass filtering of the data. The experiment is updated with the filtered signal. You can use other preprocessing tools such as remove offset, scale, and resample to further process the measured data. For this example low-pass filtering is sufficient.

Estimate Model Parameter Values

With the experiment data configured and preprocessed you can now run an estimation. First select parameters to estimate. Click theParameter Estimationtab and selectSelect Parameters. A dialog to specify model parameters for estimation opens. ClickSelect Parametersand select,C1, the circuit capacitor value. Set the capacitor minimum value to 0 and the initial guess to 460e-6.

ClickEstimateto start the estimation. You can modify estimation options by setting theCost Functioncombobox and clickingMore Options.

While the estimation is running, the plots update and a dialog showing estimation progress appears. The progress dialog shows the estimation iterations, the number of times the model has been evaluated (F-count), and the estimation cost at each iteration.

After a number of iterations the estimation converges and terminates. The model is updated with the estimated parameters and the estimation results are saved in the data browser.

相关的例子

To learn how to estimate model parameters using thesdo.optimizecommand, seeEstimate Model Parameters and Initial States (Code).

Close the model.

bdclose('sdoRCCircuit')