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
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 systems|
|Sparse State-Space Models — Represent large sparse state-space models|
|LTV and LPV Models — Represent models with varying coefficients|
|Identified LTI models — Representations of linear systems with tunable coefficients, whose values can be identified using measured input/output data.|
|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.|
|Generalized LTI models — Representations of systems that include tunable or uncertain coefficients|
|Dynamic Control Design Blocks — Tunable, uncertain, or switch analysis points for constructing models of control systems|