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Neuro-optimal control for discrete stochastic processes via a novel policy iteration algorithm 期刊论文
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 卷号: 50, 期号: 11, 页码: 3972-3985
作者:  Liang, Mingming;  Wang, Ding;  Liu, Derong
浏览  |  Adobe PDF(1604Kb)  |  收藏  |  浏览/下载：211/69  |  提交时间：2020/10/23
Adaptive critic designs  adaptive dynamic programming (ADP)  local policy iteration  neuro-dynamic programming  optimal control  stochastic processes  
Improved value iteration for neural-network-based stochastic optimal control design 期刊论文
NEURAL NETWORKS, 2020, 卷号: 124, 页码: 280-295
作者:  Liang, Mingming;  Wang, Ding;  Liu, Derong
Adobe PDF(5875Kb)  |  收藏  |  浏览/下载：261/57  |  提交时间：2020/06/02
Adaptive critic designs  Adaptive dynamic programming  Neural networks  Optimal control  Stochastic processes  Value iteration  
Model-Free Adaptive Control for Unknown Nonlinear Zero-Sum Differential Game 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 卷号: 48, 期号: 5, 页码: 1633-1646
作者:  Zhong, Xiangnan;  He, Haibo;  Wang, Ding;  Ni, Zhen
收藏  |  浏览/下载：173/0  |  提交时间：2018/10/10
Adaptive Dynamic Programming (Adp)  Globalized Dual Heuristic Dynamic Programming (Gdhp)  Model-free  Neural Networks  Zero-sum Game  
Manifold Regularized Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 932-943
作者:  Li, Hongliang;  Liu, Derong;  Wang, Ding
收藏  |  浏览/下载：190/0  |  提交时间：2018/10/10
Adaptive Dynamic Programming  Approximate Dynamic Programming  Approximate Policy Iteration (Api)  Manifold Regularization  Reinforcement Learning (Rl)  
A novel neural optimal control framework with nonlinear dynamics: Closed-loop stability and simulation verification 期刊论文
NEUROCOMPUTING, 2017, 卷号: 266, 页码: 353-360
作者:  Wang, Ding;  Mu, Chaoxu
Adobe PDF(1503Kb)  |  收藏  |  浏览/下载：330/73  |  提交时间：2018/03/03
Adaptive Dynamic Programming  Adaptive System  Learning Control  Neural Network  Optimal Regulator  Stability  
Adaptive tracking control for a class of continuous-time uncertain nonlinear systems using the approximate solution of HJB equation 期刊论文
NEUROCOMPUTING, 2017, 卷号: 260, 页码: 432-442
作者:  Mu, Chaoxu;  Sun, Changyin;  Wang, Ding;  Song, Aiguo
Adobe PDF(1555Kb)  |  收藏  |  浏览/下载：449/167  |  提交时间：2017/09/12
Adaptive Tracking Control  Hamilton-jacobi-bellman (Hjb) Equation  Adaptive Dynamic Programming (Adp)  Neural Networks  Uncertainties  
Error Bound Analysis of Q-Function for Discounted Optimal Control Problems With Policy Iteration 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 卷号: 47, 期号: 7, 页码: 1207-1216
作者:  Yan, Pengfei;  Wang, Ding;  Li, Hongliang;  Liu, Derong
Adobe PDF(625Kb)  |  收藏  |  浏览/下载：357/86  |  提交时间：2017/09/12
Adaptive Dynamic Programming (Adp)  Error Analysis  Nonlinear Systems  Policy Iteration  Q-function  
Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy 期刊论文
NEUROCOMPUTING, 2016, 卷号: 214, 页码: 297-306
作者:  Wang, Ding;  Liu, Derong;  Mu, Chaoxu;  Ma, Hongwen
Adobe PDF(1113Kb)  |  收藏  |  浏览/下载：439/123  |  提交时间：2017/02/14
Adaptive Dynamic Programming  Decentralized Control  Guaranteed Cost Control  Interconnected Systems  Learning Control  Neural Networks  Optimal Control  Uncertain Plant  
Data-Based Adaptive Critic Designs for Nonlinear Robust Optimal Control With Uncertain Dynamics 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 卷号: 46, 期号: 11, 页码: 1544-1555
作者:  Wang, Ding;  Liu, Derong;  Zhang, Qichao;  Zhao, Dongbin
Adobe PDF(1082Kb)  |  收藏  |  浏览/下载：468/203  |  提交时间：2017/02/14
Adaptive Critic Designs  Adaptive Dynamic Programming  Intelligent Control  Neural Networks  Policy Iteration  Robust Optimal Control  System Identification  Uncertain Nonlinear Systems  
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3341-3354
作者:  Luo, Biao;  Liu, Derong;  Wu, Huai-Ning;  Wang, Ding;  Lewis, Frank L.
浏览  |  Adobe PDF(3217Kb)  |  收藏  |  浏览/下载：604/213  |  提交时间：2016/11/09
Adaptive Control  Adaptive Dynamic Programming (Adp)  Data-based  Off-policy Learning  Optimal Control  Policy Gradient