Identification of Linear Error-Models with Projected Dynamical Systems

• Published in: Mathematical and computer modelling of dynamical systems Vol. 10; no. 1; pp. 59 - 91
• Main Authors: Kuhnen, K., Krejci, P.
• Format: Journal Article
• Language: English
• Published: Taylor & Francis Group 01.03.2004
• Subjects: error models; hysteresis compensation; Identification; multidimensional stop; projected dynamical systems
• ISSN: 1387-3954; 1744-5051
• DOI: 10.1080/13873950412331318071

Linear error models are an integral part of several parameter identification methods for feedforward and feedback control systems and lead in connection with the L 2 -norm to a convex distance measure which has to be minimised for identification purposes. The parameters are hereby often subject to specific restrictions whose intersections span a convex solution set with non-differentiability points on its boundary. For solving these well conditioned problems on-line the paper formulates the solution of the bounded convex minimisation problem as a stable equilibrium set of a proper system of differential equations. The vector field of the corresponding system of differential equations is based on a projection of the negative gradient of the distance measure. A general drawback of this approach is the discontinuous right-hand side of the differential equation caused by the projection transformation. The consequence are difficulties for the verification of the existence, uniqueness and stability of a solution trajectory. Therefore the first subject of this paper is the derivation of an alternative formulation of the projected dynamical system, which exhibits, in contrast to the original formulation, a continuous right-hand side and is thus accessible to conventional analysis methods. For this purpose the multi-dimensional stop operator is used and the existence, uniqueness and stability properties of the solution trajectories are established. The second part of this paper deals with the numerical integration of the projected dynamical system which is used for an implementation of the identification method on a digital signal processor for example. To demonstrate the performance the application of this on-line identification method to the hysteretic filter synthesis with the modified Prandtl-Ishlinskii approach is presented in the last part of this paper.