Dynamic System Models generally represent systems that have internal dynamics or memory of past states such as integrators, delays, transfer functions, and state-space models.
Most commands for analyzing linear systems, such as
linearSystemAnalyzer, work on most Dynamic
System Model objects. For Generalized Models, analysis commands use
the current value of tunable parameters and the nominal value of uncertain
parameters. Commands that generate response plots display random samples
of uncertain models.
The following table lists the Dynamic System Models.
|Model Family||Model Types|
|Numeric LTI models — Basic numeric representation of linear
(requires Control System Toolbox™)
|Identified LTI models — Representations of linear systems with tunable
coefficients, whose values can be identified using measured input/output
(requires System Identification Toolbox™)
|Identified nonlinear models — Representations of nonlinear systems with
tunable coefficients, whose values can be identified using input/output
data. Limited support for commands that analyze linear
(requires System Identification Toolbox)
|Generalized LTI models — Representations of systems that include tunable
or uncertain coefficients|
(tunable models require Control System Toolbox; uncertain models require Robust Control Toolbox™)
|Dynamic Control Design Blocks — Tunable, uncertain, or switch analysis
points for constructing models of control systems |
(tunable Control Design Blocks and analysis points require Control System Toolbox; uncertain Control Design Blocks require Robust Control Toolbox)