SparseModalTruncationOptions

Options for sparse model order reduction with modal truncation method

Since R2023b

Description

This object contains model order reduction options of sparse linear time-invariant models, and is contained in the Options property of a SparseModalTruncation object R created using reducespec. To configure these options, use dot notation, for example, R.Options.ModeOnly = true.

For the full workflow, see Task-Based Model Order Reduction Workflow.

Properties

Focus — Frequency range of interest

[0 inf] (default) | vector

Frequency range of interest, specified as a vector of form [fmin,fmax]. When you specify a value for this property, the algorithm computes only modes in this frequency range.

By default, the focus is unspecified ([0 inf]) and the algorithm computes the MaxOrder modes with smallest magnitude.

MaxOrder — Maximum order of modal approximation

1000 (default) | positive integer

Maximum order of the modal approximation, specified as a positive integer. This value limits the number of eigenvalues computed by the Krylov-Schur iterations and the order of the modal approximation of the original sparse model.

ModeOnly — Flag to only compute modes

false or 0 (default) | true or 1

Flag to only compute modes for the original system sys, specified as a logical 0 (false) or 1 (true).

• When R.Options.ModeOnly is true, the software computes only the pole locations, damping, and natural frequency of the poles, which correspond to the Mode, Damping, and Frequency properties of R, respectively.

• When R.Options.ModeOnly is false, the software computes a full modal decomposition and populates all properties of R.

DCFrequency — Frequency for evaluating DC contributions

0 (default) | nonnegative scalar

Frequency for evaluating and matching DC contributions, specified as a nonnegative scalar.

For models with integrators, you cannot evaluate modal contributions at DC since the DC gain is infinite. To evaluate modal contributions and match gains at a different frequency, set the property to a positive value. The default value of this property corresponds to the DC contributions.

InputScaling — Input scaling factors

[] (default) | vector

Input scaling factors, specified as a vector of length Nu, where Nu is the number of inputs in the original model sys.

Use this option to emphasize specific input channels in sys. The software evaluates the modal contributions for the scaled system.

This affects only the normalized DC contribution (R.DCGain). For the input scaling factor D_u and output scaling factor D_y, the normalized DC contribution of G_k(s) in continuous time is obtained as

$$\frac{\Vert D_y{G}_k(0)D_u\Vert }{\Vert D_{y}G(0)D_u\Vert }$$

In discrete time, the software uses the first time samples G_k(1) and G(1).

OutputScaling — Output scaling factors

[] (default) | vector

Output scaling factors, specified as a vector of length Ny, where Ny is the number of outputs in the original model sys.

Use this option to emphasize specific output channels in sys. The software evaluates the modal contributions for the scaled system.

This affects only the normalized DC contribution (R.DCGain). For the input scaling factor D_u and output scaling factor D_y, the normalized DC contribution of G_k(s) in continuous time is obtained as

$$\frac{\Vert D_y{G}_k(0)D_u\Vert }{\Vert D_{y}G(0)D_u\Vert }$$

In discrete time, the software uses the first time samples G_k(1) and G(1).

ModeTol — Accuracy of computed modes

1e-12 (default) | positive scalar

Tolerance for identifying converged eigenvalues in Krylov-Schur iterations, specified as a positive scalar.

SepTol — Relative accuracy of modal contribution

1e-12 (default) | scalar between 0 and 1

Relative accuracy of modal contribution, specified as a scalar between 0 and 1.

This option limits the condition number of the block diagonalizing transformation to roughly SepTol/eps. Increasing SepTol helps yield smaller modal components at the expense of accuracy.

Version History

Introduced in R2023b