BFO-GA Interval Type-2 Fuzzy PD Control applied to a Magnetic Levitation System

This paper presents the optimization of two fuzzy logic control (FLC) schemes applied to a magnetic levitation (MagLev) system. The controller optimization is performed using a hybrid algorithm that combines the techniques of genetic algorithms (GA) and Bacterial Foraging Optimization (BFO) algorithm. Comparisons with a type-1 fuzzy PD (T1-FPD) and an interval type-2 fuzzy PD (IT2-FPD) controllers applied to a MagLev system are addressed via simulations in MATLAB -Simulink. The obtained type-2 controllers are based on the design of type-1 fuzzy logic controllers; from these, the uncertainty is generated to have the type-2 membership functions. The control law is directly calculated from the error position signal of the steel ball, as well as its respective velocity error, which presents interesting control qualities.