Explain Model Predictive Control (MPC) and its advantages over PID.

MPC uses a dynamic model to predict future system behavior and optimizes control actions over a receding horizon while satisfying constraints. At each step, it solves an optimization problem (typically quadratic programming for linear MPC) minimizing predicted error and control effort, applies first control action, then repeats. Advantages over PID: handles MIMO systems naturally, explicitly handles constraints on inputs and outputs, accommodates preview information, and manages complex interactions. Challenges include computational load and need for accurate models. Widely used in process industries and autonomous vehicles.