## 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

## 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.