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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
Authors:  Yang, Xiong;  He, Haibo;  Liu, Derong;  Zhu, Yuanheng
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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  
Using reinforcement learning techniques to solve continuous-time non-linear optimal tracking problem without system dynamics 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2016, 卷号: 10, 期号: 12, 页码: 1339-1347
Authors:  Zhu, Yuanheng;  Zhao, Dongbin;  Li, Xiangjun
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Nonlinear Control Systems  Continuous Time Systems  Learning (Artificial Intelligence)  Optimal Control  Dynamic Programming  Lyapunov Methods  Linear Systems  Reinforcement Learning  Continuous-time Problem  Nonlinear Optimal Tracking Problem  Adaptive Dynamic Programming  Model-free Adaptive Optimal Tracking Algorithm  Lyapunov Analysis  Linear System