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This paper presents a new technique for the efficiency optimization of an interior permanent magnet synchronous generator, IPMSG, working at variable speed and load. For a given operating condition, characterized by a given turbine speed (ω ω ω ω T ) and electric torque (T e ), the search control is implemented via the "Rosenbrock" method, which determines the level of the flux current component that results in maximum output power. Once the optimal level of the flux current component is 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. 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 from the optimum point. If compared with other techniques proposed in the scientific literature, this method shows better performance, because once the fuzzy controller learns, the search for the optimum point is immediate.