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

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

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE