A new controller based on artificial neural network (ANN) for induction machines is introduced and implemented. The introduced controller is designed for efficiency maximization. The neural network (ANN) is used for commanding optimum voltage and frequency that maximizes the drive efficiency. To provide the required data to train and test the artificial neural network a simulation program was written to calculate commanded voltage and frequency that would drive the induction machine with maximum efficiency at different load and speed. The controller is able to control the induction machine over a wide speed range from standstill to high speeds in the flux-weakening region. The trained neural networks are employed for the control of an induction machine under different loads. It has been found that the neural network control system is reliable without using a speed sensor. The proposed controller is an appropriate technique for speed sensor-less control of an induction machine to drive an electric vehicle (EV). The performance of this control system has been found to be as good as those controllers, which have been used in the induction machine model. The descriptions of the control system, training procedure of the neural network is also given. Simulation results are shown to validate the scheme.