WIT Press


On Identification Of Dynamic Systems

Price

Free (open access)

Paper DOI

10.2495/CMEM950521

Volume

12

Pages

8

Published

1995

Size

459 kb

Author(s)

S.A. Lukasiewicz & R. Babaei

Abstract

On identification of dynamic systems S.A. Lukasiewicz, R. Babaei Department of Mechanical Engineering, The University of Calgary, Calgary, AB Canada T2N 1N4 Summary The method is based on the least square technique, and minimization of the global error functional. The application of the method of finite differences for the representation of all constraints and model equations, makes it possible to present the filtering and identification process in a simple and efficient mathematical form. Filtering and identification may be achieved using the mathematical optimization technique in which the distance norm is selected as the objective function and then minimized subject to the constrained to represent the state equations. The optimally conditions for this constrained optimization problem are obtained in the form of the Kuhn-Tucker equations [3, 4, 5]. These equations, in turn, can be used to determine the optimal filtering law and to identify the system. In particular

Keywords