Contents

FCMODOM

Estimates the A and C matrix in a continuous-time state-space model from frequency response function (FRF) data that was preprocessed by fcordom.

Syntax

[A,C] = fcmodom(R,n)

Description

This function estimates the A and C matrices corresponding to an n th order discrete-time LTI state-space model. The compressed data matrix R from the preprocessor function fcordom is used to this end.

Inputs

R is a compressed data matrix containing information about the measured data, as well as information regarding the system dimensions.

n is the desired model order n.

Outputs

A is the state-space model's A matrix.

C is the state-space model's C matrix.

Algorithm

The data matrix obtained with fcordom contains the weighted left singular vectors of a matrix similar to the R22 matrix (see fdordom). Unlike in the discrete-time case, the first n of these vectors do not form a direct estimate Os of the extended observability matrix. Rather, a generalized matrix Og is estimated because of the Forsythe-recursions in the data-compression step. The Ahat and Chat estimates are extracted such that this generalized shift-structure is taken into account [1].

Used By

This a top-level function that is used directly by the user.

See Also

fcordom, fdmodom

References

[1] R. Pintelon, "Frequency domain subspace system identfication using non-parametric noise models", in Proceedings of the 40th IEEE Conference on Decision and Control, Orlando, Florida, pp. 3916-3921, Dec 2001.