Control and Signal Processing Lab Seminar

Seminar/Forum

Control and Signal Processing Lab Seminar

Richard Newton Room
Electrical and Electronic Engineering Building 193

Booking not required

Further Details

T: (03) 9035 8028

cskey@unimelb.edu.au

What has Instrumental Variable (IV) methods for system identification to offer? Instrumental Variable methods can consistently identify plant models of systems operating in open- or closed-loop while relying on simple linear (regression) algorithms. IV methods are attractive when dealing with complex processes that are high-dimensional with many inputs and outputs, since they do not require non-convex optimization. In addition to this computationally desirable property, IV methods have the potential advantage that they can provide consistent plant estimate even when the noise model is mis-specified. The development and performance of IV methods will be analyzed in two frameworks: linear closed-loop system identification and open-loop system identification of LPV (Linear Parameter Varying) models. An application to rainfall/flow modeling will be discussed.

The main important (and well-known) books related to the work that will be presented are :

• L. Ljung, System Identification : Theory for the Used - Second Edition, 1999, for all the materials dedicated to the prediction error methods

• T. Söderström, P. Stoica : Instrumental Variable Methods for System Identification, 1983, Springer-Verlag

• P.C. Young : Recursive estimation and time-series analysis - Second Edition, in particular, Part II, chapter 7 (Optimal Identification and estimation of discrete-time transfer function models) and Part III Chapter 11 (State-Dependent Parameter (SDP) Estimation)

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