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Supervised assisted deep reinforcement learning for emergency voltage control of power systems 期刊论文
NEUROCOMPUTING, 2022, 卷号: 475, 页码: 69-79
作者:  Li, Xiaoshuang;  Wang, Xiao;  Zheng, Xinhu;  Dai, Yuxin;  Yu, Zhihong;  Zhang, Jun Jason;  Bu, Guangquan;  Wang, Fei-Yue
Adobe PDF(2551Kb)  |  收藏  |  浏览/下载：358/75  |  提交时间：2022/06/06
Deep reinforcement learning  Behavioral cloning  Dynamic demonstration  Emergency control  
Torque sensorless decentralized neuro-optimal control for modular and reconfigurable robots with uncertain environments 期刊论文
NEUROCOMPUTING, 2018, 卷号: 282, 页码: 60-73
作者:  Dong, Bo;  Zhou, Fan;  Liu, Keping;  Li, Yuanchun
收藏  |  浏览/下载：271/0  |  提交时间：2019/12/16
Modular and reconfigurable robot  Decentralized control  Adaptive dynamic programming (ADP)  Optimal control  Neural networks  
Bounded robust control design for uncertain nonlinear systems using single-network adaptive dynamic programming 期刊论文
NEUROCOMPUTING, 2017, 卷号: 266, 页码: 128-140
作者:  Huang, Yuzhu;  Wang, Ding;  Liu, Derong
Adobe PDF(1876Kb)  |  收藏  |  浏览/下载：362/100  |  提交时间：2018/03/03
Neural Networks  Optimal Control  Adaptive Dynamic Programming  Bounded Robust Control  Uncertain Nonlinear Systems  
Adaptive tracking control for a class of continuous-time uncertain nonlinear systems using the approximate solution of HJB equation 期刊论文
NEUROCOMPUTING, 2017, 卷号: 260, 页码: 432-442
作者:  Mu, Chaoxu;  Sun, Changyin;  Wang, Ding;  Song, Aiguo
Adobe PDF(1555Kb)  |  收藏  |  浏览/下载：465/173  |  提交时间：2017/09/12
Adaptive Tracking Control  Hamilton-jacobi-bellman (Hjb) Equation  Adaptive Dynamic Programming (Adp)  Neural Networks  Uncertainties  
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
浏览  |  Adobe PDF(1373Kb)  |  收藏  |  浏览/下载：435/118  |  提交时间：2017/05/05
Large-scale Nonlinear Systems  Partial Loss Of Actuator Effectiveness  Decentralized Fault Tolerant Control  Self-tuned Local Feedback Gain  Neural Network  
Data-driven adaptive dynamic programming for continuous-time fully cooperative games with partially constrained inputs 期刊论文
NEUROCOMPUTING, 2017, 卷号: 238, 期号: *, 页码: 377-386
作者:  Zhang, Qichao;  Zhao, Dongbin;  Zhu, Yuanheng
浏览  |  Adobe PDF(1508Kb)  |  收藏  |  浏览/下载：668/282  |  提交时间：2017/05/04
Adaptive Dynamic Programming  Optimal Control  Neural Network  Fully Cooperative Games  Data-driven  Constrained Input  
Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy 期刊论文
NEUROCOMPUTING, 2016, 卷号: 214, 页码: 297-306
作者:  Wang, Ding;  Liu, Derong;  Mu, Chaoxu;  Ma, Hongwen
Adobe PDF(1113Kb)  |  收藏  |  浏览/下载：476/127  |  提交时间：2017/02/14
Adaptive Dynamic Programming  Decentralized Control  Guaranteed Cost Control  Interconnected Systems  Learning Control  Neural Networks  Optimal Control  Uncertain Plant  
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
作者:  Shi, Guang;  Liu, Derong;  Wei, Qinglai
浏览  |  Adobe PDF(1405Kb)  |  收藏  |  浏览/下载：469/201  |  提交时间：2017/02/14
Energy Consumption  Time-series Prediction  Office Buildings  Echo State Networks  Reservoir Topologies  
Distributed control algorithm for bipartite consensus of the nonlinear time-delayed multi-agent systems with neural networks 期刊论文
NEUROCOMPUTING, 2016, 卷号: 174, 页码: 928-936
作者:  Wang, Ding;  Ma, Hongwen;  Liu, Derong
Adobe PDF(1037Kb)  |  收藏  |  浏览/下载：404/172  |  提交时间：2016/03/19
Bipartite Consensus  Distributed Control Algorithm  Multi-agent Systems  Neural Networks  Time Delays  
Neural-network-based decentralized control of continuous-time nonlinear interconnected systems with unknown dynamics 期刊论文
NEUROCOMPUTING, 2015, 期号: 165, 页码: 90-98
作者:  Liu, Derong;  Li, Chao;  Li, Hongliang;  Wang, Ding;  Ma, Hongwen
浏览  |  Adobe PDF(1120Kb)  |  收藏  |  浏览/下载：411/130  |  提交时间：2015/09/17
Adaptive Dynamic Programming  Decentralized Control  Optimal Control  Policy Iteration  Neural Networks