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Dynamic System Models

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 bode, margin, and 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 FamilyModel Types
Numeric LTI models — Basic numeric representation of linear systems
(requires Control System Toolbox™)
tf
zpk
ss
frd
pid
pidstd
pid2
pidstd2
Identified LTI models — Representations of linear systems with tunable coefficients, whose values can be identified using measured input/output data.
(requires System Identification Toolbox™)
idtf
idss
idfrd
idgrey
idpoly
idproc
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 systems.
(requires System Identification Toolbox)
idnlarx
idnlhw
idnlgrey
Generalized LTI models — Representations of systems that include tunable or uncertain coefficients
(tunable models require Control System Toolbox; uncertain models require Robust Control Toolbox™)
genss
genfrd
uss
ufrd
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)
tunableGain
tunableTF
tunableSS
tunablePID
tunablePID2
ultidyn
udyn
AnalysisPoint

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