596 citations · 807 across the 20 of their papers we have counts for
16 papers · 1 filter
Learning Free Terminal Time Optimal Closed-loop Control of Manipulators
Wei Hu, Yue Zhao, Weinan E +2
This paper presents a novel approach to learning free terminal time closed-loop control for robotic manipulation tasks, enabling dynamic adjustment of task duration and control inp…
Offline Supervised Learning V.S. Online Direct Policy Optimization: A Comparative Study and A Unified Training Paradigm for Neural Network-Based Optimal Feedback Control
Yue Zhao, Jiequn Han
This work is concerned with solving neural network-based feedback controllers efficiently for optimal control problems. We first conduct a comparative study of two prevalent approa…
Progressive Optimal Path Sampling for Closed-Loop Optimal Control Design with Deep Neural Networks
Xuanxi Zhang, Jihao Long, Wei Hu +2
Closed-loop optimal control design for high-dimensional nonlinear systems has been a long-standing challenge. Traditional methods, such as solving the associated Hamilton-Jacobi-Be…
Pandemic Control, Game Theory and Machine Learning
Yao Xuan, Robert Balkin, Jiequn Han +2
Game theory has been an effective tool in the control of disease spread and in suggesting optimal policies at both individual and area levels. In this AMS Notices article, we focus…
Solving Optimal Control Problems of Rigid-Body Dynamics with Collisions Using the Hybrid Minimum Principle
Wei Hu, Jihao Long, Yaohua Zang +2
Collisions are common in many dynamical systems with real applications. They can be formulated as hybrid dynamical systems with discontinuities automatically triggered when states…
Empowering Optimal Control with Machine Learning: A Perspective from Model Predictive Control
Weinan E, Jiequn Han, Jihao Long
Solving complex optimal control problems have confronted computational challenges for a long time. Recent advances in machine learning have provided us with new opportunities to ad…