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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
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  Li, Xiangjun
浏览  |  Adobe PDF(976Kb)  |  收藏  |  浏览/下载：451/184  |  提交时间：2016/12/26
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  
Neural-network-based online optimal control for uncertain non-linear continuous-time systems with control constraints 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2013, 卷号: 7, 期号: 17, 页码: 2037-2047
作者:  Yang, Xiong;  Liu, Derong;  Huang, Yuzhu
浏览  |  Adobe PDF(493Kb)  |  收藏  |  浏览/下载：375/96  |  提交时间：2015/08/12
Adaptive Control  Approximation Theory  Closed Loop Systems  Continuous Time Systems  Lyapunov Methods  Neurocontrollers  Nonlinear Control Systems  Optimal Control  Robust Control  Uncertain Systems  Neural Network-based Online Adaptive Optimal Control  Uncertain Nonlinear Continuous-time Systems  Control Constraints  Infinite-horizon Optimal Control Problem  Control Policy  Saturation Constraints  Identifier-critic Architecture  Hamilton-jacobi-bellman Equation Approximation  Uncertain System Dynamics  Critic Nn  Action-critic Dual Networks  Reinforcement Learning  Identifier Nn  Policy Iteration  Lyapunovaeuros Direct Method  Closed Loop System Stability