Guining Pertin

NST-RL: Residual Reinforcement Learning With Approximate Optimal Regulation for Robust Drone Control

We present NST-RL, a framework that couples residual reinforcement learning (RL) with an approximate optimal regulator computed using Nonlinear Systems Toolbox (NST) for robust control. Disturbance compensation is learned through residual corrections routed via a dynamic extension that preserves control-input positivit...