Magnetic bearings are an exciting and innovative technology that has seen considerable advances in recent years. Such systems require active control, and most often, linear techniques are used very successfully. However, there are applications where such methods have limited effectiveness and other control strategies must be considered. Fuzzy logic control performs very well in nonlinear control situations where the plant parameters are either partially or mostly unidentified. Its effectiveness for nonlinear systems also offers advantages to magnetic bearing systems. Little research has been done on non-singleton fuzzy logic systems and their application to noise rejection on magnetic bearings or rotating machinery. Non-singleton fuzzy set inputs allow one to account for input measurement uncertainty. The fuzzy logic controller’s task in this work is two-fold; provide control for stable levitation of the shaft and perform noise filtering to reduce the effects of the disturbance. The current work consist of model development, controller design, simulation and experimental validation. The basic simulation model consist of a horizontal shaft supported by a radial magnetic bearing. The magnetic bearing is modeled as a nonlinear element. The controller designs are implemented and tested using a bench-top rotor rig equipped with a radial magnetic bearing. Some representative results are presented and discussed.

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