93-120
A New Approach To Linear State Space System Identification
T. El-Ali, F. A. Scarpino and T. J. Kelly*
Abstract
Mathematical representations, or models, for dynamic systems are not constant for all time. They depend on the physical components and the surrounding environment of the system. It is well known [1] that in the absence of noise (or other uncertainty in measurement) that the state vector of a deterministic, full state estimator can be made to systematically converge to the state vector of the system under observation. The above statement is true when the
modeling, as reflected in the observer, is "perfect". When the modeling of the system under observation is less than perfect, the convergence characteristics of the observer are, in some manner, modified. A study of the behavior of the state estimator in the presence of errors in the plant model is usually undertaken. In contrast, a study of the estimation of the modified plant by the means provided in the information which may be gleaned from the modification in the convergence characteristics is undertaken in this paper. The modified plant is determined by using the "system-observer pair" error dynamics.
*The University of Dayton, 300 College Park, LK/304, Dayton, Ohio 45469.