Yuan-Qing Xia

Disturbance-Rejection Reinforcement Learning for Control of Unknown Nonlinear Systems

How to realize the ultimate boundedness during training on unknown nonlinear systems under continuous stochastic disturbances is a key challenge in reinforcement learning (RL). To this end, we propose a Lyapunov-based data-driven RL framework for disturbance rejection control and provides a step toward reliable disturb...