System Identification of Complex System Models

Funding Source

Details

Source:Australian Research Council
Duration:2010-2012
Abstract:An essential part of science, engineering and economics is the development of mathematical models to describe how certain quatities relate to one another. For example, such models have proven to be extremely powerful in predicting the value of financial instruments, and in providing high performance control of robots, and in detecting faults or changes in petrochemical processing plants. This project is directed at developing such models using modern computer based optimisation methods, but for situations that, on the one hand, have previously been considered unsolvable, and on the other, are acknowledged as being of high practical interest.

Projects Funded

System Identification Toolbox V2

This toolbox is a MATLAB-based software package for the estimation of dynamic systems. A wide range of standard estimation approaches are supported. These include the use of non-parametric, subspace-based and prediction-error algorithms coupled (in the latter case) with either MIMO state space or MISO polynomial model structures.

System Identification

Theoretical and empirical study of various problems in system identification. Particular attention is paid to robust estimation of Multivariable and Nonlinear systems, and to error quantification.

Sub-Projects

Wiener Hammerstein Benchmark

Details of our attempt at the Wiener-Hammerstein Benchmark problem

Maintained by System Identification of Complex System Models
University of Newcastle
29 Nov 2008, © Copyright