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This paper introduces a new technique for efficiency optimization of adjustable-speed drives, with an emphasis on vector-controlled induction motor drives. The technique combines two distinct control methods, namely, online search of the optimal operating point and a model-based efficiency control. For a given operating condition, which is characterized by a given speed and load torque, a search controller (SC); based on the "Rosenbrock" method) determines the flux level that results in the minimum input power. Once this optimal flux level has been found, this information is utilized to update the rule base of a fuzzy controller that 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 usual operating conditions (given by the required speeds and load torques) are identified by the SC, the rule base is progressively updated such that the fuzzy controller learns to model the optimal operating conditions for the entire torque-speed plane. As the machine parameters are subject to change during operation, the SC is kept active to track possible minor deviation of the optimum point, thus ensuring true optimal efficiency operation.