Model Predictive Control

Model Predictive Control (MPC) is an advanced control technique that optimizes control actions over a predicted future time horizon, subject to constraints. Current research emphasizes improving MPC's computational efficiency for real-time applications, particularly in robotics, through parallel computing, accelerated gradient descent, and neural network approximations (e.g., differentiable predictive control, TransformerMPC). This focus stems from MPC's importance in diverse fields, including robotics, battery management, and autonomous driving, where its ability to handle complex systems and safety constraints is crucial.