14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper WeA3.4

Young, Peter (Lancaster Univ.), Garnier, Hugues (Univ. Henri Poincaré, Nancy 1), Gilson, Marion (Univ. Henri Poincaré, Nancy 1)

An Optimal Instrumental Variable Approach for Identifying Hybrid Box-Jenkins Models

Scheduled for presentation during the Invited Session "Continuous-Time System Identification I" (WeA3), Wednesday, March 29, 2006, 11:30−11:50, Hunter Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 17, 2018

Keywords Continuous Time System Estimation


The paper describes and evaluates an optimal instrumental variable method for identifying hybrid continuous-time transfer function models of the Box-Jenkins form from discrete-time sampled data, where the relationship between the measured input and output is a continuous-time transfer function, while the noise is represented as a discrete-time AR or ARMA process. The performance of the proposed hybrid parameter estimation scheme is evaluated by Monte Carlo simulation analysis.