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Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3417-3428
Authors:  Wang, Ding;  He, Haibo;  Liu, Derong
View  |  Adobe PDF(1068Kb)  |  Favorite  |  View/Download:64/10  |  Submit date:2018/03/03
H-infinity Control  Adaptive Systems  Adaptive/approximate Dynamic Programming  Critic Network  Event-based Design  Learning Criterion  Neural Control  
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
Authors:  Shi, Guang;  Liu, Derong;  Wei, Qinglai
View  |  Adobe PDF(3253Kb)  |  Favorite  |  View/Download:141/26  |  Submit date:2017/02/23
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  
Energy consumption prediction of office buildings based on echo state networks 期刊论文
NEUROCOMPUTING, 2016, 卷号: 216, 期号: n/a, 页码: 478-488
Authors:  Shi, Guang;  Liu, Derong;  Wei, Qinglai
View  |  Adobe PDF(1405Kb)  |  Favorite  |  View/Download:125/61  |  Submit date:2017/02/14
Energy Consumption  Time-series Prediction  Office Buildings  Echo State Networks  Reservoir Topologies