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Asymptotically stable critic designs for approximate optimal stabilization of nonlinear systems subject to mismatched external disturbances 期刊论文
NEUROCOMPUTING, 2020, 卷号: 396, 页码: 201-208
作者:  Zhao, Bo;  Shi, Guang;  Wang, Ding
收藏  |  浏览/下载：187/0  |  提交时间：2020/07/06
Adaptive dynamic programming  Adaptive critic designs  Mismatched external disturbances  Disturbance observer  Optimal control  Neural networks  Nested tuning law  
Realizing human-like manipulation with a musculoskeletal system and biologically inspired control scheme 期刊论文
NEUROCOMPUTING, 2019, 卷号: 339, 期号: 暂无, 页码: 116-129
作者:  Jiahao Chen;  Shanlin Zhong;  Erlong Kang;  Hong Qiao
Adobe PDF(4018Kb)  |  收藏  |  浏览/下载：354/46  |  提交时间：2019/07/12
Human-like manipulation  Musculoskeletal system  Biologically inspired  Muscle synergy  Attractive region in environment  
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：295/62  |  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：411/157  |  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：357/120  |  提交时间：2017/09/12
Adaptive Dynamic Programming (Adp)  Guaranteed Cost Control  Neural Networks  Uncertain Dynamics  Stability  
Self-tuned local feedback gain based decentralized fault tolerant control for a class of large-scale nonlinear systems 期刊论文
NEUROCOMPUTING, 2017, 期号: 235, 页码: 147-156
作者:  Zhao, Bo;  Li, Yuanchun;  Liu, Derong
浏览  |  Adobe PDF(1373Kb)  |  收藏  |  浏览/下载：382/105  |  提交时间：2017/05/05
Large-scale Nonlinear Systems  Partial Loss Of Actuator Effectiveness  Decentralized Fault Tolerant Control  Self-tuned Local Feedback Gain  Neural Network  
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：342/135  |  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  
Distributed control algorithm for bipartite consensus of the nonlinear time-delayed multi-agent systems with neural networks 期刊论文
NEUROCOMPUTING, 2016, 卷号: 174, 页码: 928-936
作者:  Wang, Ding;  Ma, Hongwen;  Liu, Derong
Adobe PDF(1037Kb)  |  收藏  |  浏览/下载：367/153  |  提交时间：2016/03/19
Bipartite Consensus  Distributed Control Algorithm  Multi-agent Systems  Neural Networks  Time Delays  
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
浏览  |  Adobe PDF(2222Kb)  |  收藏  |  浏览/下载：601/236  |  提交时间：2015/09/23
Adaptive Dynamic Programming  Approximate  Dynamic Programming  Q-learning  Optimal Tracking Control  Neural Networks  
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
浏览  |  Adobe PDF(836Kb)  |  收藏  |  浏览/下载：271/108  |  提交时间：2015/10/13
Adaptive Dynamic Programming  Adaptive Critic Designs  Approximate Dynamic Programming  Value Iteration  Approximation Errors  Optimal Tracking Control