Model Predictive Control (MPC) is an advanced optimal trajectory control methodology that solves a constrained finite-horizon optimization problem numerically online at each discrete sampling instant. Employing a dynamic system model of the robot, the optimizer predicts future state trajectories across N forward steps while observing state boundaries and physical actuator constraints. Only the immediate first control increment is executed, continuously repeating the receding-horizon optimization cycle.