Abstract

Frequency domain subspace identification is an effective means of obtaining a low order dynamic model from frequency domain data. With noisy data several problems arise in choosing the appropriate rank and finding the low order representation. A nuclear norm (sum of the singular values) minimisation based method, using spectral constraints, is described and shown to be an effective technique for overcoming these problems.

Bio:

Roy Smith is a Professor in the Automatic Control Laboratory at the Swiss Federal Institute of Technology (ETH, Zurich) in Switzerland. From 1990 to 2010 he was on the faculty of the Electrical Engineering Dept. at the University of California, Santa Barbara. He received his undergraduate education at Canterbury University in New Zealand (1980) and a Ph.D. from the California Institute of Technology (1990).

Roy Smith’s research interests include: the identification and control of uncertain systems, and distributed estimation, communication and control systems. His application experience includes: process control, automotive engines, flexible space structures, aeromanoeuvring Mars entry vehicles, formation flying of spacecraft, magnetically levitated bearings, high energy accelerator control, and energy control for buildings. He has been a long time consultant to the NASA Jet Propulsion Laboratory on guidance, navigation and control aspects of interplanetary and deep space science spacecraft. He is a Fellow of the IEEE , an Associate Fellow of the AIAA , and a member of SIAM and NZAC .