modreal

Purpose

Modal form realization and projection

Syntax

• [G1,G2] = modreal(G,cut)
  

Description

[G1,G2] = modreal(G,cut) returns a set of state-space LTI objects G1 and G2 in modal form given a state-space G and the model size of G1, cut.

The modal form realization has its A matrix in block diagonal form with either 1x1 or 2x2 blocks. The real eigenvalues will be put in 1x1 blocks and complex eigenvalues will be put in 2x2 blocks. These diagonal blocks are ordered in ascending order based on eigenvalue magnitudes.

The complex eigenvalue a+bj is appearing as 2x2 block

• 

This table describes input arguments for modreal.

Argument	Description
G	LTI model to be reduced.
cut	(Optional) an integer to split the realization. Without it, a complete modal form realization is returned

This table lists output arguments.

Argument	Description
G1,G2	LTI models in modal form

G can be stable or unstable. , and

is calculated such that the system DC gain is preserved.

Algorithm

Using a real eigen structure decomposition reig and ordering the eigenvectors in ascending order according to their eigenvalue magnitudes, we can form a similarity transformation out of these ordered real eigenvectors such that he resulting systems G1 and/or G2 are in block diagonal modal form.

Note    This routine is extremely useful when model has j-axis singularities, e.g., rigid body dynamics. It has been incorporated inside Hankel based model reduction routines - hankelmr, balancmr, bstmr, and schurmr to isolate those j-axis poles from the actual model reduction process.

Examples

Given a continuous stable or unstable system, G, the following commands can get a set of modal form realizations depending on the split index -- cut:

• randn('state',1234); rand('state',5678);
  G = rss(50,2,2);
  [G1,G2] = modreal(G,2); % cut = 2 for two rigid body modes
  G1.d = zeros(2,2); % remove the DC gain of the system from G1
  sigma(G,G1,G2)
  

See Also

reduce      Top level model reduction routines

balancmr    Balanced truncation via square-root method

schurmr     Balanced truncation via Schur method

bstmr       Balanced stochastic truncation via Schur method

ncfmr       Balanced truncation for normalized coprime factors

hankelmr    Hankel minimum degree approximation

hankelsv    Hankel singular value

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