Continuous Time State Space Model Identification Using Closed-Loop Data

This paper focuses on identifying a continuous time state space model for a system operating in closed-loop, using a subspace method based on error-in-variables (EIV) models. The proposed approach in this paper extends the existing methods in the discrete-time systems to continuous-time systems wher...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohd-Mokhtar, R., Liuping Wang
Format: Conference Proceeding
Language:English
Subjects:
Australia
Closed loop systems
closed-loop system
continuous time
Continuous time systems
Data engineering
Filters
Iterative algorithms
Mathematical model
Predictive models
State-space methods
state-space model
System identification
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper focuses on identifying a continuous time state space model for a system operating in closed-loop, using a subspace method based on error-in-variables (EIV) models. The proposed approach in this paper extends the existing methods in the discrete-time systems to continuous-time systems where the Laguerre filters are used in the identification procedure. Furthermore, to meet the requirement for continuous time model and to remain filter causality, the choice of instrumental variable is based on the future horizon variables. Monte-Carlo simulation results are presented to verify the consistency of the estimated models.
ISSN:2376-1164
DOI:10.1109/AMS.2008.93