Wind power has many benefits over other energy sources, including a high power density and an outstanding return on investment. However, there are some drawbacks, such as intermittent output power and the need for periodic maintenance. As a result, its output is substantially variable, making it difficult to predict and potentially causing system instability. Therefore, to model such a source, it is necessary to model the dynamic behavior of the wind turbine generator as well as the characteristics of the wind speed to capture the fluctuations. Furthermore, the durability and efficiency of the wind energy conversion system (WECS) are wholly dependent on the quality of the control strategy employed. In this paper, we introduced a control scheme, which makes it possible to find an optimal solution to the control problem while at the same time operating within the constraint point. Therefore, we designed the Model Predictive Controller to control and smoothly transition the wind turbine in all its operating modes while complying with its constraints. The main objective of using this control technique is to maximize power production while keeping the control action as simple as possible. The WECS used in this study is the horizontal axis wind turbines (HAWT), which are easier to control as their dynamics are not so complicated to model and, at the same time, produce maximum output power. The controller works have to adapt in the same way as the control goals are different for different wind speeds. Gain and weight scheduling strategies are used to design a control system that allows smooth transitioning between control regions. The dynamics of the wind turbine system and the controller are designed and simulated by the MATLAB / Simulink environment.