Basic Models Used to Represent Linear Systems
Numeric LTI models are the simplest blocks that are used to represent linear systems. The objects of LTI models let users store dynamic systems in representations that are commonly used. There are some linear time-invariant model types that specifically represent PID controllers in terms of their derivative, integral and proportional coefficients.
Here are the functions that are used to model linear systems.
- Tf – it transfers the function of the model
- Zpk – This function generates and converts to the zero-pole-gain model
- Ss – This is the state-space model function
- Frd – develops and converts the frequency-response data model
- Filt – This function specifies discrete transfer function in a DSP format
- Dss – This is the descriptor state-space model function
PID (proportional integral derivative) models
Functions used to generate random models
- LTI system
- LPV system
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These are models that have parametric or tunable coefficients. Generalized tunable linear time-invariant models are used to represent tunable systems. The control design blocks represent tunable components in the control system. When the control design blocks are combined with the numeric LTI models, tunable generalized LTI models are created.
Tunable generalized LTI models are essential in the following ways:
- They can be used to model tunable low-pass filters and other parametric components of a control system
- They can also be used to model control systems with both fixed and tunable components
- You can use tunable generalized LTI models to tune control systems. You can use tuning commands such as the control system tuner app and system to design goals that you specify.
Some of the functions used in tunable models include the following:
Control design blocks functions
Generalized models functions
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