Model predictive control is an advanced control methodology that employs an explicit dynamic model of a system to predict its future outputs over a finite time horizon. It determines the optimal sequence of control actions by minimizing a cost function subject to system constraints, applying only the first computed action before repeating the optimization at the subsequent time step based on new measurements, a characteristic known as the receding horizon principle. This technique is significant for its ability to effectively manage complex, constrained, and multivariable systems in various engineering applications.