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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：248/0  |  提交时间：2019/07/12
Adaptive dynamic programming  event-based design  guaranteed cost control  optimal control  self-learning technique  
Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 6, 页码: 2099-2111
作者:  Luo, Biao;  Liu, Derong;  Wu, Huai-Ning
Adobe PDF(1045Kb)  |  收藏  |  浏览/下载：370/113  |  提交时间：2018/10/10
Adaptive Control  Adaptive Dynamic Programming  Constraints  Critic-only  Data-based  Optimal Control  Q-learning  
Neural Network Learning and Robust Stabilization of Nonlinear Systems With Dynamic Uncertainties 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 1342-1351
作者:  Wang, Ding;  Liu, Derong;  Mu, Chaoxu;  Zhang, Yun
收藏  |  浏览/下载：143/0  |  提交时间：2018/10/10
Adaptive Critic  Dynamical Uncertainty  Learning Systems  Neural Networks  Optimal Control  Robust Stabilization  
Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 1226-1238
作者:  Wei, Qinglai;  Li, Benkai;  Song, Ruizhuo
Adobe PDF(2475Kb)  |  收藏  |  浏览/下载：370/122  |  提交时间：2017/02/23
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Generalized Policy Iteration (Gpi)  Neural Networks  Neurodynamic Programming  Nonlinear Systems  Optimal Control  Reinforcement Learning  
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：173/0  |  提交时间：2018/10/10
Adaptive Dynamic Programming  Approximate Dynamic Programming  Approximate Policy Iteration (Api)  Manifold Regularization  Reinforcement Learning (Rl)