Identification of Physical Parameters of Unstable Systems: Theoretical Background

Abstract

Identification of physical parameters of unstable system is an important problem, for example in the design of its diagnostic system. In the diagnostics we usually observe the trends in physical parameters changes. Two identification methods of the state space model resulting from the physics laws are presented in the paper. First one is a modification of the Observer/Kalman Filter Identification (OKID) method (J.-N. Juang (1994). Applied System Identification, Prentice-Hall, Englewood Cliffs, NJ) and the observer/controller Markov parameters are computed. They are used to obtain the physical state-space model of the open-loop system. In the second method an AutoRegressive model with eXogenous inputs (ARX) model of the observer/controller system is identified first. To identify an ARX model on-line the classical Recursive Least-Squares (RLS) method is used.