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Model Reducer

Reduce complexity of linear time-invariant (LTI) models

Description

The Model Reducer app lets you compute reduced-order approximations of high-order LTI and sparse LTI models. Working with lower-order models can simplify analysis and control design. Simpler models are also easier to understand and manipulate. You can reduce a plant model to focus on relevant dynamics before designing a controller for the plant. Or, you can use model reduction to simplify a full-order controller.

Using any of the following methods, Model Reducer helps you reduce model order while preserving model characteristics that are important to your application:

  • Balanced truncation — Remove states with relatively small energy contributions.

  • Modal truncation — Discard modes based on their locations or DC contributions

  • Pole-zero simplification — Eliminate canceling or near-canceling pole-zero pairs.

Model Reducer provides response plots and error plots to help ensure that the reduced-order model preserves important dynamics. For more information on model reduction and why it is useful, see Model Reduction Basics.

For an alternative to the Model Reducer app that lets you interactively perform model reduction and generate code for a live script, see the Reduce Model Order task in the Live Editor.

Model Reducer app

Open the Model Reducer App

  • MATLAB® Toolstrip: On the Apps tab, under Control System Design and Analysis, click the app icon.

  • MATLAB command prompt: Enter modelReducer.

Parameters

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Balanced Truncation Tab

Specify the model you want to reduce by selecting from the Model drop-down list. The list includes all models currently in the data browser. To get a model from the MATLAB workspace into the data browser, on the Model Reducer tab, click Import Model. You can import any:

  • tf, ss, or zpk model that is proper. The model can be SISO or MIMO, and continuous or discrete.

    • Continuous-time models must not have time delays. To reduce a continuous-time model with time delays, first use pade to approximate the time delays as model dynamics.

    • Discrete-time models can have time delays. For the Balanced Truncation reduction method, the app uses absorbDelay to convert the delay into poles at z = 0 before reducing the model. The additional states are reflected in the response plot and Hankel singular-value plot.

  • Generalized model such as a genss model. The Model Reducer app uses the current or nominal value of all control design blocks in model (see getValue).

  • Sparse state-space models such as sparss and mechss models.

Note

Model Reducer assumes that the model time unit (specified in the TimeUnit property of the model) is seconds. If your model does not have TimeUnit = 'seconds', use chgTimeUnit to convert the model to seconds.

Specify the model order reduction criteria. Any value is permitted that falls between the number of unstable states in the model and the number of states in the original model. If you specify a single value, Model Reducer computes and displays the responses of a model of that order. If you specify multiple values, Model Reducer computes models of all specified orders and displays their responses on the same plot. To store reduced models in the data browser, click Save Reduced Model.

For more information, see Balanced Truncation Model Reduction.

Specify the comparison plot type.

  • Model response — Plot the model frequency response. This frequency response comparison is a Bode plot for SISO models, and a singular-value plot for MIMO models.

  • Absolute error plot — Plot the frequency response of absolute error GGr.

  • Relative error plot — Plot the frequency response of relative error G1(GGr).

For more information, see Balanced Truncation Model Reduction.

Specify the analysis plot type.

  • Hankel singular values — Bar chart of Hankel singular values and associated error bounds.

  • Energy — Bar chart of normalized state energies.

Modal Truncation Tab

Specify the model you want to reduce by selecting from the Model drop-down list. The list includes all models currently in the data browser. To get a model from the MATLAB workspace into the data browser, on the Model Reducer tab, click Import Model. You can import any:

  • tf, ss, or zpk model that is proper. The model can be SISO or MIMO, and continuous or discrete.

    • Continuous-time models must not have time delays. To reduce a continuous-time model with time delays, first use pade to approximate the time delays as model dynamics.

    • Discrete-time models can have time delays. For the Balanced Truncation reduction method, the app uses absorbDelay to convert the delay into poles at z = 0 before reducing the model. The additional states are reflected in the response plot and Hankel singular-value plot.

  • Generalized model such as a genss model. The Model Reducer app uses the current or nominal value of all control design blocks in model (see getValue).

  • Sparse state-space models such as sparss and mechss models.

For more information, see Modal Truncation Model Reduction.

Note

Reduce Model Order assumes that the model time unit (specified in the TimeUnit property of the model) is seconds. If your model does not have TimeUnit = 'seconds', use chgTimeUnit to convert the model to seconds.

Frequency range of interest, specified as a vector of form [Fmin,Fmax]. The algorithm discards all the modes outside this range.

Damping range of interest, specified as a vector of form [ζmin,ζmax]. The algorithm discards all the modes outside this range.

Minimum DC contribution bound for the reduced-order model, specified as a nonnegative scalar. The algorithm discards all the modes with normalized DC contributions smaller than this value.

Specify the comparison plot type.

  • Model response — Plot the model frequency response. This frequency response comparison is a Bode plot for SISO models, and a singular-value plot for MIMO models.

  • Absolute error plot — Plot the frequency response of absolute error GGr.

  • Relative error plot — Plot the frequency response of relative error G1(GGr).

  • Mode locations — Compare the pole locations of original and reduced models.

Specify the comparison plot type.

  • DC contribution — Bar chart of normalized DC contributions.

  • Mode location — Plot the location of the poles.

  • Mode damping and natural frequency — Plot the damping and natural frequencies of the poles.

Pole/Zero Simplification Tab

Specify the model you want to reduce by selecting from the Model drop-down list. The list includes all models currently in the data browser. To get a model from the MATLAB workspace into the data browser, on the Model Reducer tab, click Import Model. You can import any:

  • tf, ss, or zpk model that is proper. The model can be SISO or MIMO, and continuous or discrete.

    • Continuous-time models must not have time delays. To reduce a continuous-time model with time delays, first use pade to approximate the time delays as model dynamics.

    • Discrete-time models can have time delays. For the Balanced Truncation reduction method, the app uses absorbDelay to convert the delay into poles at z = 0 before reducing the model. The additional states are reflected in the response plot and Hankel singular-value plot.

  • Generalized model such as a genss model. The Model Reducer app uses the current or nominal value of all control design blocks in model (see getValue).

Set the tolerance for pole-zero cancellation by using the slider or entering a value in the text box. The value determines how close together a pole and zero must be for Model Reducer to eliminate them from the reduced model. Moving the slider to the left or entering a smaller value in the text box simplifies the model less, by cancelling fewer poles and zeros. Moving the slider to the right, or entering a larger value, simplifies the model more by cancelling poles and zeros that are further apart.

For more information, see Pole-Zero Simplification.

Specify the comparison plot type.

  • Model response — Plot the model frequency response. This frequency response comparison is a Bode plot for SISO models, and a singular-value plot for MIMO models.

  • Absolute error plot — Plot the frequency response of absolute error GGr.

  • Relative error plot — Plot the frequency response of relative error G1(GGr).

Programmatic Use

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modelReducer opens the Model Reducer app with no models in the data browser. To import a model from the MATLAB workspace, click Import Model.

modelReducer(model) opens app and imports the specified LTI model. model can be a:

  • tf, ss, or zpk model that is proper. The model can be SISO or MIMO, and continuous or discrete.

    • Continuous-time models must not have time delays. To reduce a continuous-time model with time delays, first use pade to approximate the time delays as model dynamics.

    • Discrete-time models can have time delays. For the Balanced Truncation reduction method, the app uses absorbDelay to convert the delay into poles at z = 0 before reducing the model. The additional states are reflected in the response plot and Hankel singular-value plot.

  • Generalized model such as a genss model. The Model Reducer app uses the current or nominal value of all control design blocks in model (see getValue).

  • Sparse state-space models such as sparss and mechss models.

modelReducer(model1,...,modelN) opens the app and imports the specified models.

modelReducer(sessionFile) opens the app and loads a previously saved session. sessionFile is the name of a session data file in the current working directory or on the MATLAB path.

To save session data to disk, in the Model Reducer app, on the Model Reducer tab, click Save Session. The saved session data includes the current plot configuration and all models in the data browser.

Version History

Introduced in R2016a

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See Also

Functions

Live Editor Tasks