Composite modeling of transfer functions

• The problem under consideration is how to estimate the frequency function of a system and the associated estimation error when a set of possible model structures is given and when one of them is known to contain the true system. The 'classical' solution to this problem is to, firstly, use a consistent model structure selection criterium to discard all but one single structure. Secondly, estimate a model in this structure and, thirdly, conditioned on the assumption that the chosen structure contains the true system, compute an estimate of the estimation error. However, for a finite data set one cannot guarantee that the correct structure is chosen and this 'structural' uncertainty is lost in the previously mentioned approach. In this contribution a method is developed that combines the frequency function estimates and the estimation errors from all possible structures into a joint estimate and estimation error. Hence, this approach by-passes the structure selection problem. This is accomplished by employing a Bayesian setting.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Nyckelord

Data structures

Errors

Estimation

Frequency domain analysis

Identification (control systems)

Mathematical models

Regression analysis

Bayesian setting

Composite modeling

Estimation error

Finite data set

Frequency function

Transfer functions

SRA - ICT

SRA - Informations- och kommunikationsteknik

Automatic control

TECHNOLOGY

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)