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Reinforcement Learning-Based Optimal Stabilization for Unknown Nonlinear Systems Subject to Inputs With Uncertain Constraints 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 10, 页码: 4330-4340
作者:  Zhao, Bo;  Liu, Derong;  Luo, Chaomin
收藏  |  浏览/下载：195/0  |  提交时间：2021/01/07
Nonlinear systems  Optimal control  Artificial neural networks  Actuators  Observers  Feedforward systems  Adaptive dynamic programming (ADP)  neural networks (NNs)  optimal control  reinforcement learning (RL)  uncertain input constraints  unknown nonlinear systems  
Learning and Guaranteed Cost Control With Event-Based Adaptive Critic Implementation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 12, 页码: 6004-6014
作者:  Wang, Ding;  Liu, Derong
收藏  |  浏览/下载：252/0  |  提交时间：2019/07/12
Adaptive dynamic programming  event-based design  guaranteed cost control  optimal control  self-learning technique  
Neural robust stabilization via event-triggering mechanism and adaptive learning technique 期刊论文
NEURAL NETWORKS, 2018, 卷号: 102, 页码: 27-35
作者:  Wang, Ding;  Liu, Derong
收藏  |  浏览/下载：182/0  |  提交时间：2018/10/10
Adaptive Critic Designs  Adaptive Dynamic Programming  Event-triggered Control  Neural Networks  Robust Stabilization  Uncertainties  
Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems 期刊论文
NEURAL NETWORKS, 2018, 卷号: 97, 页码: 11-18
作者:  Wang, Ding;  Liu, Derong;  Zhang, Yun;  Li, Hongyi
收藏  |  浏览/下载：202/0  |  提交时间：2018/10/10
Adaptive Critic Designs  Dynamical Uncertainty  Learning Systems  Neural Networks  Optimal Control  Robust Tracking Control  
Reinforcement learning solution for HJB equation arising in constrained optimal control problem 期刊论文
NEURAL NETWORKS, 2015, 卷号: 71, 期号: 0, 页码: 150-158
作者:  Luo, Biao;  Wu, Huai-Ning;  Huang, Tingwen;  Liu, Derong
浏览  |  Adobe PDF(530Kb)  |  收藏  |  浏览/下载：448/195  |  提交时间：2016/03/30
Constrained Optimal Control  Data-based  Off-policy Reinforcement Learning  Hamilton-jacobi-bellman Equation  The Method Of Weighted Residuals