14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper FrA4.2

Domenico, Bellomo (Pol. di Bari), Babuska, Robert (Delft Univ. of Tech.), Naso, David (Pol. di Bari)

Adaptive Fuzzy Control for Speed-Reference Tracking in Non-Linear Servo Drives

Scheduled for presentation during the Regular Session "Iterative and Adaptive Control" (FrA4), Friday, March 31, 2006, 10:50−11:10, Cummings Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 16, 2018

Keywords Identification for Control, Nonlinear System Identification, Grey Box Modelling


Adaptive fuzzy control (AFC) has been an active research area over the last decade and several stable adaptive fuzzy controllers have been proposed in the literature. Such controllers are generally based on feedback linearization and their parameters are updated by tracking error-based adaptive laws, designed by Lyapunov synthesis. However, most of AFC schemes have only been evaluated on relatively simple simulations examples. In this paper, we study and compare different indirect adaptive schemes (linear and fuzzy, with standard and with composite adaptive laws), by means of an experimental benchmark consisting of two coupled servo drives. Parametric and structural changes are introduced to the controlled plant, in order to emphasize the advantages and limitations of the considered adaptive controllers. Experimental results demonstrate that AFC achieves significantly better tracking performance than the linear adaptive controller and that the composite adaptive laws provide a further improvement over the standard adaptive laws.