Loss Minimization of Induction Generators With Adaptive Fuzzy Controller

Abstract

In this paper a new technique for efficiency optimization of induction generator working at variable speed and load is introduced. The technique combines two distinct control methods, namely, on-line search of the optimal operating point, with a model based efficiency control. For a given operating condition, characterized by a given turbine speed (ω T) and electric torque (T e), the search control is implemented via the "Rosenbrock" method, which determines the flux level that results in the maximum output power. Once the optimal flux level has been found, this information is used to update the rule base of a fuzzy controller, which plays the role of an implicit mathematical model of the system. Initially, for any load condition the rule base yields the rated flux value. As the optimum points associated with the different operating conditions are identified, the rule base is progressively updated, so that the fuzzy controller learns to model the optimal operating conditions for the entire torque-speed plane. After every rule base update, the Rosenbrock controller output is reset, but it is kept active to track possible minor deviations of the optimum point.