Ma, W: Semi-Blind Robust Identification and Model Validation
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Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
01.12.2008
Verlag
VDMSeitenzahl
108
Maße (L/B/H)
22/15/0,6 cm
Gewicht
177 g
Sprache
Deutsch
ISBN
978-3-639-10983-2
We study a semi-blind robust identification
motivated from the fact that sometimes only partial
input data is exactly known. Derived from a
time-domain algorithm for robust identification, this
semi-blind robust identification
is stated as a non convex problem. We develop a
convex relaxation, by combining two variables into a
new variable, to reduce it to an LMI optimization
problem. Applying this convex relaxation, a
macro-economy modeling problem can be solved. The
problem of identification of Wiener Systems, a
special type of nonlinear systems, is analyzed from a
set-membership standpoint. We propose an algorithm
for time-domain based identification by pursuing a
risk-adjusted approach to reduce it to a convex
optimization problem. An arising non-trivial problem
in computer vision, tracking a human in a sequence of
frames, can be solved by modeling the plant as
Wiener system using the proposed identification
method. The book can serve as a reference for
financial engineers and finance-oriented
professionals in macro-economics and a textbook for
graduate courses on robust control theory and
macro-economics.
motivated from the fact that sometimes only partial
input data is exactly known. Derived from a
time-domain algorithm for robust identification, this
semi-blind robust identification
is stated as a non convex problem. We develop a
convex relaxation, by combining two variables into a
new variable, to reduce it to an LMI optimization
problem. Applying this convex relaxation, a
macro-economy modeling problem can be solved. The
problem of identification of Wiener Systems, a
special type of nonlinear systems, is analyzed from a
set-membership standpoint. We propose an algorithm
for time-domain based identification by pursuing a
risk-adjusted approach to reduce it to a convex
optimization problem. An arising non-trivial problem
in computer vision, tracking a human in a sequence of
frames, can be solved by modeling the plant as
Wiener system using the proposed identification
method. The book can serve as a reference for
financial engineers and finance-oriented
professionals in macro-economics and a textbook for
graduate courses on robust control theory and
macro-economics.
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