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Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 6, 页码: 2099-2111
作者:  Luo, Biao;  Liu, Derong;  Wu, Huai-Ning
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Adaptive Control  Adaptive Dynamic Programming  Constraints  Critic-only  Data-based  Optimal Control  Q-learning  
Data-Based Optimal Control for Weakly Coupled Nonlinear Systems Using Policy Iteration 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2018, 卷号: 48, 期号: 4, 页码: 511-521
作者:  Li, Chao;  Liu, Derong;  Wang, Ding
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Adaptive Dynamic Programming (Adp)  Neural Networks (Nns)  Optimal Control  Policy Iteration (Pi)  Unknown Dynamics  Weakly Coupled Systems  
Distributed algorithm for dissensus of a class of networked multiagent systems using output information 期刊论文
SOFT COMPUTING, 2018, 卷号: 22, 期号: 1, 页码: 273-282
作者:  Ma, Hongwen;  Liu, Derong;  Wang, Ding;  Yang, Xiong;  Li, Hongliang;  Derong Liu
浏览  |  Adobe PDF(925Kb)  |  收藏  |  浏览/下载:391/141  |  提交时间:2017/05/03
Distributed Control  Dissensus  Multiagent Systems  Output Feedback  
Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 1, 页码: 37-50
作者:  Zhang, Qichao;  Zhao, Dongbin;  Wang, Ding
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Adaptive Dynamic Programming (Adp)  Event-based Control  Neural Network (Nn)  Robust Control  Unmatched Uncertainties  
Optimal control for discrete-time systems with actuator saturation 期刊论文
OPTIMAL CONTROL APPLICATIONS & METHODS, 2017, 卷号: 38, 期号: 6, 页码: 1071-1080
作者:  Lin, Qiao;  Wei, Qinglai;  Zhao, Bo
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Approximate Dynamic Programming  Discrete Time  Generalized Policy Iteration  Optimal Control  Saturating Actuators  
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3341-3354
作者:  Luo, Biao;  Liu, Derong;  Wu, Huai-Ning;  Wang, Ding;  Lewis, Frank L.
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Adaptive Control  Adaptive Dynamic Programming (Adp)  Data-based  Off-policy Learning  Optimal Control  Policy Gradient  
Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 卷号: 64, 期号: 5, 页码: 4110-4120
作者:  Wei, Qinglai;  Liu, Derong;  Lewis, Frank L.;  Liu, Yu;  Zhang, Jie
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Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Mixed Iteration  Optimal Control  Policy Iteration  Smart Grid  Value Iteration  
Self-tuned local feedback gain based decentralized fault tolerant control for a class of large-scale nonlinear systems 期刊论文
NEUROCOMPUTING, 2017, 期号: 235, 页码: 147-156
作者:  Zhao, Bo;  Li, Yuanchun;  Liu, Derong
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Large-scale Nonlinear Systems  Partial Loss Of Actuator Effectiveness  Decentralized Fault Tolerant Control  Self-tuned Local Feedback Gain  Neural Network  
Echo state network-based Q-learning method for optimal battery control of offices combined with renewable energy 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 7, 页码: 915-922
作者:  Shi, Guang;  Liu, Derong;  Wei, Qinglai
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Recurrent Neural Nets  Neurocontrollers  Learning (Artificial Intelligence)  Office Environment  Optimal Control  Solar Power  Energy Consumption  Time Series  Secondary Cells  Energy Management Systems  Function Approximation  Echo State Network-based Q-learning Method  Optimal Battery Control  Renewable Energy  Optimal Energy Management  Solar Energy  Energy Consumption  Energy Demand  Time Series  Real-time Electricity Rate  Periodic Functions  Q-function  Optimal Charging Strategy  Optimal Discharging Strategy  Optimal Idle Strategy  Numerical Analysis  
Observer based adaptive dynamic programming for fault tolerant control of a class of nonlinear systems 期刊论文
INFORMATION SCIENCES, 2017, 期号: 384, 页码: 21-33
作者:  Zhao, Bo;  Liu, Derong;  Li, Yuanchun
浏览  |  Adobe PDF(1581Kb)  |  收藏  |  浏览/下载:360/131  |  提交时间:2017/05/05
Adaptive Dynamic Programming  Fault Tolerant Control  Policy Iteration  Nonlinear Systems  Fault Observer  Neural Network