MPC Controller

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 through techniques like neural network approximations of the prediction horizon and GPU parallelization for faster problem solving, as well as enhancing its adaptability and robustness via methods such as goal-conditioned terminal value learning and meta-reinforcement learning for controller updates. These advancements are significantly impacting diverse fields, enabling real-time control in applications ranging from robotics and autonomous driving to industrial automation and secure multi-party machine learning.