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Isoperimetric Constraint Inference for Discrete-Time Nonlinear Systems Based on Inverse Optimal Control 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2024, 页码: 1 - 13
作者:  Wei, Qinglai;  Li, Tao;  Zhang, Jie;  Li, Hongyang;  Wang, Xin;  Xiao, Jun
Adobe PDF(1700Kb)  |  收藏  |  浏览/下载：2/0  |  提交时间：2024/05/28
A Parallel Control Method For Zero-Sum Games With Unknown Time-varying System 期刊论文
The International Journal of Intelligent Control and Systems, 2023, 页码: 5页
作者:  Qinglai Wei;  Zhenhua Zhu;  Jie Zhang;  Feiyue Wang
Adobe PDF(470Kb)  |  收藏  |  浏览/下载：136/54  |  提交时间：2023/12/15
Self-Learning Optimal Control for Ice-Storage Air Conditioning Systems via Data-Based Adaptive Dynamic Programming 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 卷号: 68, 期号: 4, 页码: 3599-3608
作者:  Wei, Qinglai;  Liao, Zehua;  Song, Ruizhuo;  Zhang, Pinjia;  Wang, Zhuo;  Xiao, Jun
Adobe PDF(3395Kb)  |  收藏  |  浏览/下载：380/39  |  提交时间：2021/03/02
Optimal control  Air conditioning  Load modeling  Neural networks  Dynamic programming  Predictive models  Adaptive dynamic programming (ADP)  cooling load prediction  ice-storage air conditioning (IAC)  neural network  optimal 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
Adobe PDF(2123Kb)  |  收藏  |  浏览/下载：444/144  |  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  
Online reinforcement learning for continuous-state systems 专著章节/文集论文
出自: Frontiers of Intelligent Control and Information Processing, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore:World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, 2014
作者:  Yuanheng Zhu;  Zhao DB(赵冬斌)
Adobe PDF(24150Kb)  |  收藏  |  浏览/下载：250/27  |  提交时间：2017/09/13
Model-Free Optimal Tracking Control via Critic-Only Q-Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 卷号: 27, 期号: 10, 页码: 2134-2144
作者:  Luo, Biao;  Liu, Derong;  Huang, Tingwen;  Wang, Ding;  Luo,Biao
浏览  |  Adobe PDF(1521Kb)  |  收藏  |  浏览/下载：586/287  |  提交时间：2016/10/24
Critic-only Q-learning (Coql)  Model-free  Nonaffine Nonlinear Systems  Optimal Tracking Control  
Model-free adaptive dynamic programming for optimal control of discrete-time affine nonlinear system 会议论文
Proceedings of International Federation of Automatic Control 2014, South Africa, 2014-08
作者:  Xia ZP(夏中谱);  Dongbin Zhao
浏览  |  Adobe PDF(156Kb)  |  收藏  |  浏览/下载：289/81  |  提交时间：2016/06/16
Model-free Adaptive Dynamic Programming  Reinforcement Learning  Policy Iteration  Multilayer Perceptron Neural Network.  
Online approximate solution of HJI equation for unknown constrained-input nonlinear continuous-time systems 期刊论文
INFORMATION SCIENCES, 2016, 卷号: 328, 页码: 435-454
作者:  Yang, Xiong;  Liu, Derong;  Ma, Hongwen;  Xu, Yancai
浏览  |  Adobe PDF(833Kb)  |  收藏  |  浏览/下载：422/119  |  提交时间：2016/01/18
Adaptive Dynamic Programming  Hamilton-jacobi-isaacs Equation  Input Constraint  Neural Network  Optimal Control  Reinforcement Learning  
Action dependent heuristic dynamic programming based residential energy scheduling with home energy inter-exchange 期刊论文
ENERGY CONVERSION AND MANAGEMENT, 2015, 卷号: 103, 期号: x, 页码: 553-561
作者:  Xu, Yancai;  Liu, Derong;  Wei, Qinglai;  Qinglai Wei
浏览  |  Adobe PDF(809Kb)  |  收藏  |  浏览/下载：313/109  |  提交时间：2015/10/13
Action Dependent Heuristic Dynamic Programming  Residential Energy Management  Energy Scheduling  Control Sequence  Control Strategy  
Direct adaptive control for a class of discrete-time unknown nonaffine nonlinear systems using neural networks 期刊论文
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2015, 卷号: 25, 期号: 12, 页码: 1844-1861
作者:  Yang, Xiong;  Liu, Derong;  Wei, Qinglai;  Wang, Ding
浏览  |  Adobe PDF(1488Kb)  |  收藏  |  浏览/下载：259/85  |  提交时间：2015/09/23
Adaptive Control  Discrete-time  Nonaffine System  Nn  Feedback Control  Online Learning  Mimo  Lyapunov Method