Composite-Gradient Learning for Shared Control Authority Between Deep Reinforcement Learning and Model Predictive Control

Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining their complementary capabilities. DRL learns control policies through interaction with the environment. MPC uses a system model to optimize control