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Blockchain-Based Water-Energy Transactive Management With Spatial-Temporal Uncertainties
期刊论文
IEEE TRANSACTIONS ON SMART GRID, 2023, 卷号: 14, 期号: 4, 页码: 2903-2920
作者:
Zhao, Pengfei
;
Li, Shuangqi
;
Hu, Paul Jen-Hwa
;
Gu, Chenghong
;
Lu, Shuai
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2023/11/17
Blockchain
spatial-temporal ambiguity set
two-stage framework
water-energy nexus
A Fully Distributed Hybrid Control Framework For Non-Differentiable Multi-Agent Optimization
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 10, 页码: 1792-1800
作者:
Xia Jiang
;
Xianlin Zeng
;
Jian Sun
;
Jie Chen
;
Yue Wei
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2022/09/08
Distributed algorithm
hybrid framework
multi-agent network
non-differentiable optimization
Optimal Synchronization Control of Heterogeneous Asymmetric Input-Constrained Unknown Nonlinear MASs via Reinforcement Learning
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 3, 页码: 520-532
作者:
Lina Xia
;
Qing Li
;
Ruizhuo Song
;
Hamidreza Modares
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  |  
浏览/下载:43/0
  |  
提交时间:2022/03/09
Asymmetric input-constrained
heterogeneous nonlinear multiagent systems (MASs)
Hamilton-Jacobi-Bellman (HJB) equation
novel observer
reinforcement learning (RL)
Fast rotated BSOR method for block two-by-two linear systems with application to PDE-constrained optimal control problems
期刊论文
BIT NUMERICAL MATHEMATICS, 2022
作者:
Liang, Zhao-Zheng
;
Dou, Yan
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  |  
浏览/下载:13/0
  |  
提交时间:2022/03/01
Block two-by-two linear system
Kronecker structure
Iterative solution method
Preconditioning
PDE-constrained optimization
Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:
Hu, Guangzheng
;
Zhu, Yuanheng
;
Zhao, Dongbin
;
Zhao, Mengchen
;
Hao, Jianye
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  |  
浏览/下载:30/0
  |  
提交时间:2022/01/27
Bandwidth
Protocols
Reinforcement learning
Task analysis
Optimization
Communication networks
Multi-agent systems
Event trigger
limited bandwidth
multi-agent communication
multi-agent reinforcement learning (MARL)
ON DISCRETE SHAPE GRADIENTS OF BOUNDARY TYPE FOR PDE-CONSTRAINED SHAPE OPTIMIZATION
期刊论文
SIAM JOURNAL ON NUMERICAL ANALYSIS, 2021, 卷号: 59, 期号: 3, 页码: 1510-1541
作者:
Gong, Wei
;
Zhu, Shengfeng
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2021/10/26
shape optimization
shape gradient
boundary formulation
boundary correction
a priori error estimate
finite element
Average Quasi-Consensus Algorithm for Distributed Constrained Optimization: Impulsive Communication Framework
期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 1, 页码: 351-360
作者:
He, Xing
;
Yu, Junzhi
;
Huang, Tingwen
;
Li, Chuandong
;
Li, Chaojie
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  |  
浏览/下载:16/0
  |  
提交时间:2020/03/30
Distributed optimization
impulsive average quasi-consensus algorithm
impulsive communication framework
multiagent networks
Fine-Grained Resource Provisioning and Task Scheduling for Heterogeneous Applications in Distributed Green Clouds
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2020, 卷号: 7, 期号: 5, 页码: 1380-1393
作者:
Haitao Yuan
;
MengChu Zhou
;
Qing Liu
;
Abdullah Abusorrah
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  |  
浏览/下载:13/0
  |  
提交时间:2021/03/11
Bees algorithm
data centers
distributed green cloud (DGC)
energy optimization
intelligent optimization
simulated annealing
task scheduling
machine learning
Modeling and Task-Oriented Optimization of Contact-Aided Continuum Robots
期刊论文
IEEE/ASME Transactions on Mechatronics, 2020, 卷号: 25, 期号: 3, 页码: 1444-1455
作者:
Gao AZ(高安柱)
;
Li JH(李建华)
;
Zhou YY(周圆圆)
;
Wang ZD(王志东)
;
Liu H(刘浩)
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  |  
浏览/下载:20/0
  |  
提交时间:2020/07/11
Asymmetric configuration
contact-aided compliant mechanism
continuum robots
mechanical model
task-oriented optimization
Adaptive Exact Penalty Design for Constrained Distributed Optimization
期刊论文
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2019, 卷号: 64, 期号: 11, 页码: 4661-4667
作者:
Zhou, Hongbing
;
Zeng, Xianlin
;
Hong, Yiguang
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  |  
浏览/下载:8/0
  |  
提交时间:2020/05/24
Optimization
Distributed algorithms
Linear programming
Convex functions
Adaptive control
Convergence
Adaptive algorithms
Adaptive algorithm
convex and nondifferentiable function
distributed optimization
exact penalty method
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