The following table lists the representations of parametric models you can develop by using the System Identification VIs.

Parametric models describe systems in terms of difference or differential equations, depending on whether a system is represented by a discrete or continuous model. Compared to nonparametric models, parametric models might provide a more accurate estimation if you have prior knowledge about the system dynamics to determine model orders, time delays, and so on.

Each representation supports one or more input-output configurations: Single-Input Single-Output (SISO), Multiple-Input Single-Output (MISO), and Multiple-Input Multiple-Output (MIMO).

Table 4. Parametric Model Representations and Supported Input-Output Configurations
SISOMISOMIMO
General-LinearXX
Autoregressive (AR) X
Autoregressive with exogenous terms (ARX) XXX
Autoregressive moving average with exogenous terms (ARMAX) XX
Box-JenkinsXX
Output-ErrorXX
Transfer FunctionXX
Zero-Pole-GainXX
State-SpaceXXX