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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
Adobe PDF(2123Kb)  |  Favorite  |  View/Download:140/46  |  Submit date: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  
Online reinforcement learning control by Bayesian inference 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2016, 卷号: 10, 期号: 12, 页码: 1331-1338
Authors:  Xia, Zhongpu;  Zhao, Dongbin;  Dongbin Zhao
Adobe PDF(1559Kb)  |  Favorite  |  View/Download:132/46  |  Submit date:2016/06/15
Learning Systems  Bayes Methods  Gaussian Processes  Optimal Control  Online Reinforcement Learning Control  Bayesian Inference  Self-learning Control  Probability  Action Value Function  Gaussian Process  Bayesian-state-action-reward-state-action Algorithm