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Adaptive dynamic programming-based stabilization of nonlinear systems with unknown actuator saturation 期刊论文
NONLINEAR DYNAMICS, 2018, 卷号: 93, 期号: 4, 页码: 2089-2103
作者:  Zhao, Bo;  Jia, Lihao;  Xia, Hongbing;  Li, Yuanchun
浏览  |  Adobe PDF(1069Kb)  |  收藏  |  浏览/下载:392/139  |  提交时间:2018/10/10
Adaptive Dynamic Programming  Unknown Actuator Saturation  Continuous-time Nonlinear Systems  Stabilizing Control  Neural Networks  
Adaptive Critic Nonlinear Robust Control: A Survey 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3429-3451
作者:  Wang, Ding;  He, Haibo;  Liu, Derong
浏览  |  Adobe PDF(1954Kb)  |  收藏  |  浏览/下载:428/146  |  提交时间:2018/03/03
Adaptive Critic Designs  Adaptive/approximate Dynamic Programming (Adp)  Boundedness  Convergence  Neural Networks  Optimal Control  Reinforcement Learning  Robust Control  Stability  
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:350/95  |  提交时间:2018/03/03
Neural Networks  Optimal Control  Adaptive Dynamic Programming  Bounded Robust Control  Uncertain Nonlinear Systems  
Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3417-3428
作者:  Wang, Ding;  He, Haibo;  Liu, Derong
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H-infinity Control  Adaptive Systems  Adaptive/approximate Dynamic Programming  Critic Network  Event-based Design  Learning Criterion  Neural Control  
Event-Driven Adaptive Robust Control of Nonlinear Systems With Uncertainties Through NDP Strategy 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 卷号: 47, 期号: 7, 页码: 1358-1370
作者:  Wang, Ding;  Mu, Chaoxu;  He, Haibo;  Liu, Derong
Adobe PDF(1425Kb)  |  收藏  |  浏览/下载:392/143  |  提交时间:2017/09/12
Adaptive Dynamic Programming (Adp)  Adaptive Robust Control  Critic Neural Network  Event-driven Control  Neural Dynamic Programming (Ndp)  Uncertain Nonlinear Systems  
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:356/86  |  提交时间:2017/09/12
Adaptive Dynamic Programming (Adp)  Error Analysis  Nonlinear Systems  Policy Iteration  Q-function  
Data-driven adaptive dynamic programming for continuous-time fully cooperative games with partially constrained inputs 期刊论文
NEUROCOMPUTING, 2017, 卷号: 238, 期号: *, 页码: 377-386
作者:  Zhang, Qichao;  Zhao, Dongbin;  Zhu, Yuanheng
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Adaptive Dynamic Programming  Optimal Control  Neural Network  Fully Cooperative Games  Data-driven  Constrained Input  
Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 1, 页码: 37-50
作者:  Zhang, Qichao;  Zhao, Dongbin;  Wang, Ding
浏览  |  Adobe PDF(2233Kb)  |  收藏  |  浏览/下载:550/249  |  提交时间:2017/05/04
Adaptive Dynamic Programming (Adp)  Event-based Control  Neural Network (Nn)  Robust Control  Unmatched Uncertainties  
An Incremental Change Detection Test Based on Density Difference Estimation 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 卷号: 49, 期号: 10, 页码: 2714-2726
作者:  Bu, Li;  Zhao, Dongbin;  Alippi, Cesare
浏览  |  Adobe PDF(1601Kb)  |  收藏  |  浏览/下载:432/153  |  提交时间:2017/05/04
Change Detection  Incremental Computing  Incremental Least Squares Density Difference Change Detection Method (Lsdd-inc)  Probability Density Function (Pdf)-free  
A pdf-Free Change Detection Test Based on Density Difference Estimation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 2, 页码: 324-334
作者:  Bu, Li;  Alippi, Cesare;  Zhao, Dongbin
浏览  |  Adobe PDF(2468Kb)  |  收藏  |  浏览/下载:387/112  |  提交时间:2017/05/04
Concept Drift  Least Squares Density-difference (Lsdd)-based Method  Probability Density Function (Pdf)-free  Three-level Threshold Mechanism