User`s guide

Identifying Low-Order Transfer Functions (Process M odels)

You can create different model structures by varying the number of poles,

adding an integrator, or adding or removing a tim e delay or a zero. Y ou can

specify a ﬁrst-, second-, or third-order model, and the poles can be real or

complex (underdamped modes).

Note Continuous-time process models let you estimate the input delay.

For example, the followin g model structure is a ﬁrst-order continuous-time

process model, where K is the static gain, T

is a time constant, and T

is the

input-to-output delay:

()=

−

To learn more about estimating continuous-time process models in the G UI,

see “Tutorial – Identifying Low-Order Transfer Functions (Process Models)

Using the GUI” in System Identiﬁ cation Toolbox Getting Started Guide.

Data Supported by a Process Model

You can estimate low -order (up to third order), continuous-time transfer

functions from data with the following characteristics:

• Time- or frequency-domain

iddata or idfrd data object

• Real data, or complex data in the time domain o nly

• Single-output data

You m us t import your data into the MA TLAB workspace , as described in

Chapter 1, “Data Processing”.

How to Estimate Process Models Using the GUI

The following procedure assumes that you have already imported your data

into the GUI and performed any necessary preprocessing operations. For

more information, see Chapter 1, “Data Processing”.

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