About This Tutorial

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Objectives Data Description

Objectives

Estimate and validate linear models from single-input/single-output (SISO) data to find the one that best describes the system dynamics.

After completing this tutorial, you will be able to accomplish the following tasks using the System Identification Tool GUI:

• Import data arrays from the MATLAB workspace into the GUI.

• Plot the data.

• Process data by removing offsets from the input and output signals.

• Estimate, validate, and compare linear models.

• Export models to the MATLAB workspace.

Note   The tutorial uses time-domain data to demonstrate how you can estimate linear models. The same workflow applies to fitting frequency-domain data.

This tutorial is based on the example in section 17.3 of System Identification: Theory for the User, Second Edition, by Lennart Ljung, Prentice Hall PTR, 1999.

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Data Description

This tutorial uses the data file dryer2.mat, which contains single-input/single-output (SISO) time-domain data from Feedback Process Trainer PT326. The input and output signals each contain 1000 data samples.

This system heats the air at the inlet using a mesh of resistor wire, similar to a hair dryer. The input is the power supplied to the resistor wires, and the output is the air temperature at the outlet.

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Tutorial – Identifying Linear Models Using the GUI

Preparing Data for System Identification

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