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:

1973-02-01

Pagination or Media Count:

71.0

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