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This chapter presents a nonlinear intelligent predictive control using multi-step prediction model for the electrical motor-based yaw system of an industrial wind turbine. The proposed method introduces a finite control set under constraints for the demanded yaw rate, predicts the multi-step yaw error using the control set element and the prediction wind directions, and employs an exhaustive search method to search the control output candidate giving the minimal value of the objective function. As the objective function is designed for a joint power and actuator usage optimization, the weighting factor in the objective function is optimally determined by the fuzzy regulator that is optimized by an intelligent algorithm. Finally, the proposed method is demonstrated by simulation tests using real wind direction data.