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CASIA OpenIR
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Spiking Adaptive Dynamic Programming with Poisson Process 会议论文
, 中国山东省青岛市, 2021-07-18
作者:  Wei QL(魏庆来);  Han LY(韩立元);  Zhang TL(张铁林)
Adobe PDF(2334Kb)  |  收藏  |  浏览/下载：31/9  |  提交时间：2024/05/28
A New Constrained Cost Value Iteration for Optimal Control of Discrete-Time Nonlinear Systems 会议论文
, Beijing, China, 2021.10.22-24
作者:  Li, Tao;  Wei, Qinglai
Adobe PDF(865Kb)  |  收藏  |  浏览/下载：28/15  |  提交时间：2024/05/28
Spiking Adaptive Dynamic Programming Based on Poisson Process for Discrete-Time Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 11
作者:  Wei, Qinglai;  Han, Liyuan;  Zhang, Tielin
Adobe PDF(2904Kb)  |  收藏  |  浏览/下载：216/9  |  提交时间：2022/01/27
Maximum likelihood estimation (MLE)  Nonlinear systems  Optimal control  Poisson process  Spike train  Spiking Adaptive dynamic programming（SADP）  
Decentralized Event-Driven Constrained Control Using Adaptive Critic Designs 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:  Yang, Xiong;  Zhu, Yuanheng;  Dong, Na;  Wei, Qinglai
Adobe PDF(1578Kb)  |  收藏  |  浏览/下载：219/10  |  提交时间：2022/01/27
Adaptive critic designs (ACDs)  adaptive dynamic programming (ADP)  decentralized event-driven control  input constraint  reinforcement learning (RL)  
Discrete-Time Non-Zero-Sum Games With Completely Unknown Dynamics 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 卷号: 51, 期号: 6, 页码: 2929-2943
作者:  Song, Ruizhuo;  Wei, Qinglai;  Zhang, Huaguang;  Lewis, Frank L.
收藏  |  浏览/下载：227/0  |  提交时间：2021/08/15
Adaptive critic designs  adaptive dynamic programming  approximate dynamic programming  discrete-time  nonzero-sum (NZS)  off-policy  reinforcement learning (RL)  
Consensus Control of Leader-Following Multi-Agent Systems in Directed Topology With Heterogeneous Disturbances 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 2, 页码: 423-431
作者:  Wei, Qinglai;  Wang, Xin;  Zhong, Xiangnan;  Wu, Naiqi
Adobe PDF(4423Kb)  |  收藏  |  浏览/下载：309/46  |  提交时间：2021/03/08
Consensus control  directed topology  external disturbance  multi-agent (MA) systems