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A novel optimal tracking control scheme for a class of discrete-time nonlinear systems using generalised policy iteration adaptive dynamic programming algorithm 期刊论文
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2017, 卷号: 48, 期号: 3, 页码: 525-534
作者:  Lin, Qiao;  Wei, Qinglai;  Liu, Derong
浏览  |  Adobe PDF(296Kb)  |  收藏  |  浏览/下载：319/133  |  提交时间：2017/02/14
Adaptive Dynamic Programming  Affine Nonlinear Systems  Discrete-time  Generalised Policy Iteration  Neural Network  Tracking Control  
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 3, 页码: 840-853
作者:  Wei, Qinglai;  Liu, Derong;  Lin, Hanquan;  Derong Liu
浏览  |  Adobe PDF(2015Kb)  |  收藏  |  浏览/下载：375/162  |  提交时间：2016/06/14
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Neural Networks  Neuro-dynamic Programming  Optimal Control  Reinforcement Learning  Value Iteration  
An Approximate Optimal Control Approach for Robust Stabilization of a Class of Discrete-Time Nonlinear Systems With Uncertainties 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 卷号: 46, 期号: 5, 页码: 713-717
作者:  Wang, Ding;  Liu, Derong;  Li, Hongliang;  Luo, Biao;  Ma, Hongwen
浏览  |  Adobe PDF(328Kb)  |  收藏  |  浏览/下载：377/111  |  提交时间：2016/04/08
Adaptive Dynamic Programming (Adp)  Generalized Hamilton-jacobi-bellman (Ghjb) Equation  Neural Networks  Optimal Control  Robust Control  Successive Approximation Method  Uncertainties  
Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2015, 卷号: 45, 期号: 12, 页码: 1577-1591
作者:  Liu, Derong;  Wei, Qinglai;  Yan, Pengfei
浏览  |  Adobe PDF(1540Kb)  |  收藏  |  浏览/下载：229/70  |  提交时间：2016/03/19
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Generalized Policy Iteration  Neural Networks  Neuro-dynamic Programming  Nonlinear Systems  Optimal Control  Reinforcement Learning