On the Design of Fuzzy Based Iterative Learning Controllers for Induction Motor Drives

This paper investigates the feasibility and performance of applying fuzzy based iterative learning control (ILC) algorithms in advanced control applications of induction motors. Based on different motor operating conditions, the proposed new control scheme using the proportional-integral controller plus iterative learning control algorithms is designed with the aid of on-line parameters tuning on a fuzzy controller and the particle swarm optimization (PSO) technique. The mathematical formulation of an induction motor and the design theory of the proposed adaptive ILC control scheme are firstly described Then, comprehensive computer simulations and practical hardware tests are performed to demonstrate the unique features of the proposed control scheme. In this paper, the feasibility and performance of the proposed intelligent control schemes are compared with the conventional PI controllers in terms of speed tracking errors and robustness when a special periodic disturbance is encountered In hardware implementations, several complex computational and signal processing tasks are accomplished using the TI DSP2812 chip. The simulation tasks and hardware implementation of controllers with various test examples are carried out via a personal computer, DSP and the VisSim software environment. Typical simulation and experimental results are presented to show the effectiveness of the proposed control scheme. Copyright (C) 2010 Praise Worthy Prize S.r.l. - All rights reserved.