STATE-SPACE MODEL IDENTIFICATION OF DETERMINISTIC NONLINEAR-SYSTEMS -NONLINEAR MAPPING TECHNOLOGY AND APPLICATION OF THE LYAPUNOV THEORY

This paper investigates the state-space mapping-based framework to ide ntify deterministic nonlinear systems. The main intent is to introduce an innovative identification inroad by using nonlinear error mappings and to explore the theoretical aspects of the application of Lyapunov 's stability theory to systematically explore the convergence. This ap proach offers innovative and promising results. The Lyapunov stability theory has been widely used in stability analysis, and this paper dem onstrates the application of the second method from parameter converge nce perspectives. The systematic identification concept is introduced, and a novel scheme is developed by applying nonlinear error mappings. Another contribution is to demonstrate that in order to analyze the c onvergence, the nonquadratic Lyapunov candidates can be used. The unkn own parameters of an electric drive, actuated by a permanent-magnet sy nchronous motor, are identified by using the experimental data. The ex ample supports the procedure, and the simulation shows that the model dynamics match the experimentally measured states. (C) 1998 Elsevier S cience Ltd. All rights reserved.