Seminar at the Automatic Control Laboratory, ETH 2019


Algorithms using multi-step least-squares as an alternative to maximum likelihood and prediction error estimation of rational linear models have been around for than half a century, starting with Durbin’s classical work on MA-models. In this talk we review the different strands of such methods that exist and elucidate on their relations. We also compare these methods with the popular subspace identification approach. We also highlight Weighted Null Space Fitting, the last contribution to this type of algorithms and show some recent results for MIMO and network system identification.

Zuich, Switzerland
Håkan Hjalmarsson
Professor of Signal Processing

My research interests cover system identification, process modeling and control, and communication network