4 papers
Learning-Based Stable Optimal Control for Infinite-Time Nonlinear Regulation Problems
Han Wang, Di Wu, Lin Cheng +2
Infinite-time nonlinear optimal regulation control is widely utilized in aerospace engineering as a systematic method for synthesizing stable controllers. However, conventional met…
Confidence-Aware Learning Optimal Terminal Guidance via Gaussian Process Regression
Han Wang, Donghe Chen, Tengjie Zheng +2
Modern aerospace guidance systems demand rigorous constraint satisfaction, optimal performance, and computational efficiency. Traditional analytical methods struggle to simultaneou…
Adviser-Actor-Critic: Eliminating Steady-State Error in Reinforcement Learning Control
Donghe Chen, Yubin Peng, Tengjie Zheng +3
High-precision control tasks present substantial challenges for reinforcement learning (RL) algorithms, frequently resulting in suboptimal performance attributed to network approxi…
Stability Enhancement in Reinforcement Learning via Adaptive Control Lyapunov Function
Donghe Chen, Han Wang, Lin Cheng +1
Reinforcement Learning (RL) has shown promise in control tasks but faces significant challenges in real-world applications, primarily due to the absence of safety guarantees during…