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Policy Iteration for H infinity Optimal Control of Polynomial Nonlinear Systems via Sum of Squares Programming 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 卷号: 48, 期号: 2, 页码: 500-509
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  Yang, Xiong;  Zhang, Qichao
Adobe PDF(892Kb)  |  收藏  |  浏览/下载：284/34  |  提交时间：2018/10/10
Adaptive Dynamic Programming (Adp)  h Infinity Optimal Control  Policy Iteration (Pi)  Polynomial Nonlinear Systems  Sum Of Squares (Sos)  
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：425/141  |  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  
Policy Iteration for Hinfinity Optimal Control of Polynomial Nonlinear Systems via Sum of Squares Programming 期刊论文
IEEE Transactions on Cybernetics, 2017, 期号: PP, 页码: 1-9
作者:  Yuanheng Zhu;  Zhao DB(赵冬斌)
浏览  |  Adobe PDF(894Kb)  |  收藏  |  浏览/下载：326/158  |  提交时间：2017/09/13
Adaptive Dynamic Programming (Adp)  H∞ Optimal Control  Policy Iteration (Pi)  Polynomial Nonlinear Systems  Sum Of Squares (Sos)  
深度强化学习综述：兼论计算机围棋的发展 期刊论文
控制理论与应用, 2016, 卷号: 33, 期号: 6, 页码: 701-717
作者:  赵冬斌;  邵坤;  朱圆恒;  李栋;  陈亚冉;  王海涛;  刘德荣;  周彤;  王成红
浏览  |  Adobe PDF(2816Kb)  |  收藏  |  浏览/下载：1724/634  |  提交时间：2017/09/13
深度强化学习  初弈号  深度学习  强化学习  人工智能