The main aim of this work is to develop the Direct Torque Control (DTC) method for use with the doubly fed induction machine (DFIM) in wind power generation. In this chapter, a novel DFIM control approach is suggested based on the Dual DTC using two artificial neural networks (ANN) controllers to avoid the use of the switching tables. In addition, a new combined DDTC-ANN approach using PI controller optimized by genetic algorithm is presented. The genetic algorithm selects PI parameters that optimize the performances of traditional DTC method, then the best PI parameters are used in online mode. Indeed, the devised method seeks to enhance the efficiency of the traditional DDTC method while guaranteeing the minimum of ripple torque. Comparing the simulation results to the traditional DDTC method, it is evident that a considerable improvement in the torque fluctuation and flux response is guaranteed.