A Fast Z Transformation Algorithm for System Identification

Publisher Website
Google Scholar
Abstract
Algorithms for system identification and the computation of its mathematical model through a ``fast'' Z transformation of its sampled response in the presence of noise are introduced. It is shown that by iteratively applying constant-damping-and constant-frequency contour finite Z transforms a system's mathematical model-in the presence of noise can be efficiently evaluated. On line tracking of the poles and zeros of relatively rapidly time-variant systems such as a space shuttle or a jet aircraft are possible applications. An organization for a high-speed machine including a fast Fourier transform processor for on line identification of relatively rapidly time-variant system is suggested. Applications of the described algorithms include enhancement of poles in spectral analysis of signals, representation of signals by poles and zeros for signal classification, coding and recognition, filter synthesis, adaptive filtering, identification of parameters in curve fitting problems, in addition to system identification in the presence of noise. The procedure presented here is a transform domain approach that is distinct, to the knowledge of the author, when compared to known identification techniques in which a best fitting is made to an assumed mathematical model of the system. In addition to the smoothing obtained here through the computation of spectra in the Z plane of a time series including redundancy, no priori knowledge of the order of the system needs be assumed.

This publication has 8 references indexed in Scilit: