CEC Faculty Articles

Title

Indirect Continuous-Time System Identification - A Subspace Downsampling Approach

Event Date/Location

Orlando, FL

Document Type

Article

Date

12-2011

Publication Title

50th IEEE Conference on Decision and Control and European Control Conference

First Page

6463

Last Page

6468

Description

This article presents a new indirect identification method for continuous-time systems able to resolve the problem of fast sampling. To do this, a Subspace IDentification Down-Sampling (SIDDS) approach that takes into consideration the intermediate sampling instants of the input signal is proposed. This is done by partitioning the data set into m subsets, where m is the downsampling factor. Then, the discrete-time model is identified using a based subspace identification discrete-time algorithm where the data subsets are fused into a single one. Using the algebraic properties of the system, some of the parameters of the continuous-time model are directly estimated. A procedure that secures a prescribed number of zeros for the continuous-time model is used during the estimation process. The algorithm's performance is illustrated through an example of fast sampling, where its performance is compared with the direct methods implemented in Contsid.

DOI

10.1109/CDC.2011.6160622

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