| Abstract |
Adaptive control for high-performance drives systems is today an important subject of research. AC
drives requiring good position command tracking and load regulation responses are increasingly
demanded in industrial applications. The tracking and regulation accuracies should not be affected by
parameter uncertainties, unknown load variations or external disturbances. This can only be achieved
by an adaptive type control because of the loading conditions, inertias and system parameters are all
changing during the motion. Generally the adaptation is attainted by using either the model reference
approach or recursive plant parameters identification, but they present complex algorithms and low
responses respectively.
In this paper is developed and tested a Self-Tuning Adaptive Speed Controller for AC drives with a
very low computational algorithm. The authors propose a self-tuning control based on a supervisory
fuzzy adaptation. The supervisor continuously monitors the status of the system through the error and
its derivative and changes the Ki parameter of an standard PDF controller for adapting it to the plant
evolution according to the dynamics of the system.
The fuzzy logic adaptive strategy has been readily implemented, with very fast learning features and
very good tracking and regulation characteristics. The stability analysis of the developed controller has
been also carried out, and experimental results demonstrate the robustness of the suggested algorithm
in contending with varying load and torque disturbance. |
