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CATEGORIES:CUED Control Group Seminars
SUMMARY:Optimal experiment design for open and closed loop
identification - Professor Michel Gevers (Univers
ité catholique de Louvain)
DTSTART;TZID=Europe/London:20100504T140000
DTEND;TZID=Europe/London:20100504T150000
UID:TALK23670AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/23670
DESCRIPTION:Optimal experiment design for system identificatio
n was a very active research topic in the 1970’s :
the results at that time focused on the minimizat
ion of different measures of the parameter covaria
nce matrix. The research on this topic disappeare
d from the horizon for more than a decade. In the
mid eighties new results became available that foc
used on quality criteria that took account of the
objective for which the model was estimated. These
results were based on approximate variance formul
ae for the estimated transfer functions\, under th
e assumption that the model order goes to infinity
. Experiment design experienced a sudden revival o
f activity from around 2003 under a triple influe
nce : the advent of new expressions for the varian
ce of estimated quantities that did not require an
assumption of model order going to infinity\, t
he introduction of the concept of « least costly i
dentification design»\, and the development of n
ew optimal design techniques for identification th
at convert the optimization problem into semi-de
finite programs that can be solved using Linear Ma
trix Inequalities. In this talk we shall first re
view the development of optimal experiment design.
We shall then present new results that allow one
to solve the optimal closed loop experiment design
problem\, where the optimization is performed joi
ntly with respect to the controller and the spectr
um of the external excitation. Our results are bas
ed on the partial positive definite matrix complet
ion theorem.
LOCATION:Cambridge University Engineering Department\, LR5
CONTACT:Dr Ioannis Lestas
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