Study of fuzzy network position controller

The fuzzy neural network (FNN) position controller based on the Sugeno fuzzy model is presented. The position controller is applied for the brushless electrical DC machine (BLDCM) serve system for the first time. During the experiments, the controller´s performances, such as precision, astringency and control performances, are studied. The fuzzy neural network position controller is compared with the proportion position controller. Simulation results show that the FNN position controller is more precise and less time-consuming for convergence and control performances, when parametric uncertainties, disturbance and unmodeled dynamics exist at the same time. The robust and the ability suppressing disturbances are better. The effect on the tracing performance is satisfactory.