Accession Number : AD0756271

Title :   Model Structure Determination and Identifiability Problems in System Identification.

Descriptive Note : Annual rept.,

Corporate Author : SYSTEMS CONTROL INC PALO ALTO CALIF

Personal Author(s) : Tse,Edison T. S. ; Weinert,Howard L. ; Anton,John J. ; Mehra,Raman K.

Report Date : FEB 1973

Pagination or Media Count : 71

Abstract : The canonical structure of linear systems is examined and specific canonical forms are constructed. It is shown that although a general stochastic model is not identifiable, its associated steady-state kalman filter is identifiable if a canonical form is used. A non-iterative method is developed for estimating the parameters (including model order and noise covariance) of a steady-state Kalman filter. Finally, the concept of local identifiability is discussed and sufficient conditions are derived for local identifiability of parameters in terms of the Fisher information matrix. (Author)

Descriptors :   (*ADAPTIVE CONTROL SYSTEMS, MATHEMATICAL MODELS), LINEAR SYSTEMS, IDENTIFICATION SYSTEMS, STOCHASTIC PROCESSES, INPUT OUTPUT DEVICES, MATRICES(MATHEMATICS), WHITE NOISE, THEOREMS

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE