Dr. David Westwick

System identification can be described as the act of learning models of dynamic systems from measured input/output data. It was originally developed in a control systems context where identified models of the plant could be used in controller design.  Initial work was limited to linear time-invariant systems.  This has since expanded to consider systems that are nonlinear and/or time-varying.  Network identification, which considers structures comprising multiple overlapping feedback loops, is a recent development in the field of system identification.  Given a particular topology, as well as the available output measurements and manipulated inputs, it can determine which of the elements in the system are identifiable, as well as methods for identifying those subsystems. This talk will use a pipeline monitoring application as a case study.  A network approach will be used to develop and identify a model of sound propagation in and around a pipeline, given distributed measurements from a fibre-optic sensor. This identified model can then be used in leak detection and pipeline monitoring applications.

Biography:

Dr. Westwick received the B.A.Sc. degree in Engineering Physics from The University of British Columbia (1986), and the M.Sc.E. and PhD. degrees in Electrical Engineering from The University of New Brunswick (1988) and McGill University (1995), respectively.  His doctorate was followed by postdoctoral fellowships in the Department of Biomedical Engineering at Boston University, and the Systems and Control Engineering Group at Delft University of Technology. Since 1999, he has been a faculty member in the Department of Electrical and Computer Engineering at the Schulich School of Engineering, where he is currently holds the rank of Professor.   He served as an Associate Dean in the Faculty of Graduate Studies, and then as Head of the Department of Electrical and Computer Engineering, both at the University of Calgary.

He has held appointments as a Visiting Scholar at the Department of Fundamental Electricity and Instrumentation (ELEC) at the Vrije Universiteit Brussel, and at the Sensory Motor Performance Lab at the Rehabilitation Institute of Chicago / Northwestern University. His research interests include developing system identification techniques for diverse applications ranging from neuromuscular control and robotics to power systems and electrical machines.  His publications include over 150 papers in peer-reviewed journals and international conferences, as well as the book “Identification of Nonlinear Physiological Systems” (2003) published by John Wiley and Sons as part of the IEEE Engineering in Medicine and Biology Society book series.   He is a Fellow of Engineers Canada, an Honourary Fellow of Geoscientists Canada, and a Senior Member of the IEEE.