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Design of an adaptive nonlinear control system for high performance induction motors is developed in this paper. The proposed control system is of the explicit model reference type. It consists of a nonlinear controller (inner loop) that controls the rotor speed, an adaptation mechanism (outer loop) that involves a maximum likelihood estimator, communicating with a feedback control law that uses the results of the adaptation mechanism to redesign the inner loop controller online. The advantage of synthesizing this type of controller lies in the fact that the desired trajectory of the rotor speed is determined from the output of the reference model, while the control trajectories that lead to that behavior are computed through the developed state feedback control law. The control system is simulated under a situation where some of the parameters vary in the presence of noise. It is shown that the adaptive controller keeps the performance of the drive system close to the desired performance even in the presence of uncertainty. The effect of measurement noise is also taken into consideration to show that the controller is feasible for practical situations.