Model Predictive Control (MPC) is an advanced, optimization-based control strategy for managing complex dynamic systems. At each control interval, MPC uses an internal dynamic model of the plant to predict its future behavior over a finite prediction horizon. It then solves a constrained optimization problem—minimizing a cost function (e.g., tracking error, energy use) while respecting operational limits—to compute a sequence of optimal control actions. Only the first control input from this sequence is applied to the system before the process repeats at the next time step, a principle known as receding horizon control. This allows MPC to proactively account for future events and constraints.




