报告摘要：
Abstract: A well known difficulty in frequency domain system identification over a large bandwidth is the ill-conditioning of the normal matrix. This typically manifests itself as poor or erroneous estimates. Several methods have been proposed in the literature for addressing this issue. However, none appear to give an entirely satisfactory solution. Here we present a novel technique, utilising particular basis functions, aimed specifically at improving the numerical properties of the least squares normal matrix in parameter estimation over a large dynamic range. We show that, under some mild assumptions, the achieved condition number for the proposed method is actually independent of the frequency range. Several examples are presented showing the superior performance of the proposed method when applied to large dynamic range estimation problems.

报告人简介： 
James Welsh was born in Maitland, Australia. He received the B.E. degree (Hons. I) in electrical engineering from The University of Newcastle, Australia. Dr. Welsh received his PhD in 2004, which studied ill-conditioning problems arising in system identification, from the same university. During the last several years, he has been actively involved in research projects at the Centre for Complex Dynamic Systems and Control, The University of Newcastle, involving System Identification, Model Predictive Control and Powertrain Control. His research interests span across system identification and control system design. Recent projects have taken him into the modelling and simulation of biological systems and also areas of rehabilitation. He is currently with the School of Electrical Engineering and Computer Science, The University of Newcastle.

联系人:贾庆山
jiaqs@tsinghua.edu.cn