14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper WeB3.4

Yuz, Juan I. (The Univ. of Newcastle), Goodwin, Graham C. (The Univ. of Newcastle)

Sampled-Data Models for Stochastic Nonlinear Systems

Scheduled for presentation during the Invited Session "Continuous-Time System Identification II" (WeB3), Wednesday, March 29, 2006, 16:30−16:50, 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 22, 2018

Keywords Continuous Time System Estimation, Nonlinear System Identification, Grey Box Modelling


To carry out identification of continuous-time models one inevitably needs to work with a sampled-data description of a system. In this paper a sampled-data model to represent continuous-time stochastic nonlinear systems is proposed. The model is simple to obtain and accurate in a well defined sense. It is based on numerical solution of stochastic differential equations, and shows some connections to the linear case. The results here extend previous work by the authors for the (nonlinear) deterministic case.