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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
浏览  |  Adobe PDF(1068Kb)  |  收藏  |  浏览/下载：418/110  |  提交时间：2018/03/03
H-infinity Control  Adaptive Systems  Adaptive/approximate Dynamic Programming  Critic Network  Event-based Design  Learning Criterion  Neural Control  
Adaptive dynamic programming for robust neural control of unknown continuous-time non-linear systems 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 14, 页码: 2307-2316
作者:  Yang, Xiong;  He, Haibo;  Liu, Derong;  Zhu, Yuanheng
浏览  |  Adobe PDF(2123Kb)  |  收藏  |  浏览/下载：426/141  |  提交时间：2017/09/13
Dynamic Programming  Robust Control  Neurocontrollers  Continuous Time Systems  Control System Synthesis  Nonlinear Control Systems  Optimal Control  Function Approximation  Monte Carlo Methods  Closed Loop Systems  Asymptotic Stability  Adaptive Dynamic Programming  Robust Neural Control Design  Unknown Continuous-time Nonlinear Systems  Ct Nonlinear Systems  Adp-based Robust Neural Control Scheme  Robust Nonlinear Control Problem  Nonlinear Optimal Control Problem  Nominal System  Adp Algorithm  Actor-critic Dual Networks  Control Policy Approximation  Value Function Approximation  Actor Neural Network Weights  Critic Nn Weights  Monte Carlo Integration Method  Closed-loop System  Asymptotically Stability