Model Reduction

Model order reduction, low-order approximation, pole-zero cancellation

Working with lower-order models can simplify analysis and control design. Simpler models are also easier to understand and manipulate than high-order models. High-order models obtained by linearizing complex Simulink^® models, interconnecting model elements, or other sources can contain states that do not contribute much to the dynamics of particular interest to your application. Use the Model Reducer app, the Reduce Model Order task in the Live Editor, or functions such as balred and minreal to reduce model order while preserving model characteristics that are important for your application.

For more information about ways to reduce model order, see Model Reduction Basics.

Apps

Model Reducer

Reduce complexity of linear time-invariant (LTI) models

Live Editor Tasks

Reduce Model Order

Reduce complexity of linear time-invariant (LTI) models in the Live Editor

Functions

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Approximation

`balred`	Model order reduction
`balredOptions`	Create option set for model order reduction
`balreal`	Gramian-based input/output balancing of state-space realizations
`hsvd`	(Not recommended) Hankel singular values of dynamic system
`hsvplot`	Plot Hankel singular values and return plot handle
`hsvdOptions`	(Not recommended) Create option set for computing Hankel singular values and input/output balancing

Simplification

`minreal`	Minimal realization or pole-zero cancellation
`sminreal`	Structural pole/zero cancellations
`modred`	Eliminate states from state-space models

Mode Selection

`freqsep`	Slow-fast decomposition
`freqsepOptions`	Options for slow-fast decomposition

Topics

Model Reduction Basics
Model-order reduction can simplify analysis and control design by providing simpler models that are easier to understand and manipulate.
Reduce Model Order Using the Model Reducer App
Interactively reduce model order while preserving important dynamics.
Model Reduction in the Live Editor
Interactively perform model reduction and generate code in a live script using the Reduce Model Order task.
Balanced Truncation Model Reduction

Compute lower-order approximations of higher-order models by removing states with lower energy contributions.
Pole-Zero Simplification
Reduce model order by canceling pole-zero pairs or eliminating states that have no effect on the overall model response.
Mode-Selection Model Reduction
Reduce model order by eliminating poles that fall outside a specific frequency range.
Visualize Reduced-Order Models in the Model Reducer App
Examine and compare time-domain and frequency-domain responses of the original and reduced models.