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Bounded robust control design for uncertain nonlinear systems using single-network adaptive dynamic programming 期刊论文
NEUROCOMPUTING, 2017, 卷号: 266, 页码: 128-140
作者:  Huang, Yuzhu;  Wang, Ding;  Liu, Derong
Adobe PDF(1876Kb)  |  收藏  |  浏览/下载：362/100  |  提交时间：2018/03/03
Neural Networks  Optimal Control  Adaptive Dynamic Programming  Bounded Robust Control  Uncertain Nonlinear Systems  
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：340/77  |  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：463/172  |  提交时间：2017/09/12
Adaptive Tracking Control  Hamilton-jacobi-bellman (Hjb) Equation  Adaptive Dynamic Programming (Adp)  Neural Networks  Uncertainties  
Neural-network-based adaptive guaranteed cost control of nonlinear dynamical systems with matched uncertainties 期刊论文
NEUROCOMPUTING, 2017, 卷号: 245, 页码: 46-54
作者:  Mu, Chaoxu;  Wang, Ding
Adobe PDF(1843Kb)  |  收藏  |  浏览/下载：382/131  |  提交时间：2017/09/12
Adaptive Dynamic Programming (Adp)  Guaranteed Cost Control  Neural Networks  Uncertain Dynamics  Stability  
Event-based input-constrained nonlinear H infinity state feedback with adaptive critic and neural implementation 期刊论文
NEUROCOMPUTING, 2016, 卷号: 214, 期号: *, 页码: 848-856
作者:  Wang, Ding;  Mu, Chaoxu;  Zhang, Qichao;  Liu, Derong
浏览  |  Adobe PDF(1090Kb)  |  收藏  |  浏览/下载：380/143  |  提交时间：2017/02/14
Adaptive Critic Learning (Acl)  Adaptive Dynamic Programming (Adp)  Event-based Control  Hamilton-jacobi-isaacs (Hji) Equation  Input Constraints  Neural Networks  Nonlinear H-infinity Control  State Feedback  
Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors 期刊论文
NEUROCOMPUTING, 2015, 卷号: 149, 期号: x, 页码: 106-115
作者:  Wei, Qinglai;  Liu, Derong;  Qinglai Wei
Adobe PDF(836Kb)  |  收藏  |  浏览/下载：311/123  |  提交时间：2015/10/13
Adaptive Dynamic Programming  Adaptive Critic Designs  Approximate Dynamic Programming  Value Iteration  Approximation Errors  Optimal Tracking Control  
Nonlinear neuro-optimal tracking control via stable iterative Q-learning algorithm 期刊论文
NEUROCOMPUTING, 2015, 卷号: 168, 期号: x, 页码: 520-528
作者:  Wei, Qinglai;  Song, Ruizhuo;  Sun, Qiuye;  Qinglai Wei
Adobe PDF(2222Kb)  |  收藏  |  浏览/下载：655/243  |  提交时间：2015/09/23
Adaptive Dynamic Programming  Approximate  Dynamic Programming  Q-learning  Optimal Tracking Control  Neural Networks  
Nearly finite-horizon optimal control for a class of nonaffine time-delay nonlinear systems based on adaptive dynamic programming 期刊论文
NEUROCOMPUTING, 2015, 卷号: 156, 期号: x, 页码: 166-175
作者:  Song, Ruizhuo;  Wei, Qinglai;  Sun, Qiuye;  Qinglai Wei
浏览  |  Adobe PDF(629Kb)  |  收藏  |  浏览/下载：396/110  |  提交时间：2015/09/21
Adaptive Dynamic Programming  Approximate Dynamic Programming  Adaptive Critic Designs  Nonlinear Systems  Optimal Control  Time-delay  
Neural-network-based decentralized control of continuous-time nonlinear interconnected systems with unknown dynamics 期刊论文
NEUROCOMPUTING, 2015, 期号: 165, 页码: 90-98
作者:  Liu, Derong;  Li, Chao;  Li, Hongliang;  Wang, Ding;  Ma, Hongwen
浏览  |  Adobe PDF(1120Kb)  |  收藏  |  浏览/下载：410/130  |  提交时间：2015/09/17
Adaptive Dynamic Programming  Decentralized Control  Optimal Control  Policy Iteration  Neural Networks  
Finite-horizon neuro-optimal tracking control for a class of discrete-time nonlinear systems using adaptive dynamic programming approach 期刊论文
NEUROCOMPUTING, 2012, 卷号: 78, 期号: 1, 页码: 14-22
作者:  Wang, Ding;  Liu, Derong;  Wei, Qinglai
Adobe PDF(465Kb)  |  收藏  |  浏览/下载：273/97  |  提交时间：2015/08/12
Adaptive Critic Designs  Adaptive Dynamic Programming  Approximate Dynamic Programming  Finite-horizon Optimal Tracking Control  Learning Control  Neural Networks  Reinforcement Learning