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检索条件"机构=Control and Process Engineering"
4498 条 记 录,以下是81-90 订阅
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A Depression Level Classification Model Based on EEG and GCN Network with Domain Generalization  43
A Depression Level Classification Model Based on EEG and GCN...
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43rd Chinese control Conference, CCC 2024
作者: Zhang, Zhongyi Xu, Chenyang Jin, Licheng Hou, Huirang Meng, Qinghao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China
Electroencephalography (EEG) contains a wealth of information, including neuron activity, allowing for a partial understanding of the brain's state. As a reliable tool, EEG, combined with deep neural networks, has... 详细信息
来源: 评论
Model Predictive control Based Reference Generation for Optimal Proportional Integral Derivative control  32
Model Predictive Control Based Reference Generation for Opti...
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32nd Mediterranean Conference on control and Automation, MED 2024
作者: Gashi, Fatos Abuibaid, Khalil Ruskowski, Martin Wagner, Achim KaiserslauternD-67663 Germany RPTU Kaiserslautern-Landau Machine Tools and Control Systems Department of Mechanical and Process Engineering KaiserslauternD-67663 Germany
We introduce an alternative approach towards optimal proportional integral derivative (PID) control, consisting of model predictive control (MPC) based reference generation. To this end, we have integrated the referen... 详细信息
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Learning to traverse challenging terrain using BGRU-Attention
Learning to traverse challenging terrain using BGRU-Attentio...
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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023
作者: Liu, Huazheng Xu, Yanbin Dong, Jiajun Dong, Feng Tianjin University Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin300072 China
In this paper, we present a model-free deep reinforcement learning (DRL) algorithm to control the locomotion of a quadruped robot adaptively at challenging terrain. This approach is used to improve the robot's abi...
来源: 评论
Monocular 3D Object Detection Based on Pseudo-LiDAR Point Cloud for Autonomous Vehicles  41
Monocular 3D Object Detection Based on Pseudo-LiDAR Point Cl...
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第41届中国控制会议
作者: Yijing Wang Sheng Xu Zhiqiang Zuo Zheng Li Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information EngineeringTianjin University
Pseudo-LiDAR point clouds are generated from monocular *** with the point cloud from LiDAR,it can provide denser *** to the inaccuracy of depth estimation,there is still a performance gap between the pseudo-LiDAR poin... 详细信息
来源: 评论
Comprehensive evaluation of an ionic liquid based deep purification process for NH_(3)-containing industrial gas
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Journal of Environmental Sciences 2024年 第2期136卷 698-708页
作者: Guoxiong Zhan Fei Cao Jianjun Chen Zhen Chen Yuanmeng Duan Fei Chang Shaojuan Zeng Yinge Bai Zengxi Li Xiangping Zhang Junhua Li State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China Sino-Danish College University of Chinese Academy of SciencesBeijing 100049China Institute of Process Engineering Chinese Academy of SciencesBeijing 100190China College of Chemical and Engineering University of Chinese Academy of SciencesBeijing 100049China
Ammonia(NH_(3))emission has caused serious environment issues and aroused worldwide *** emerging ionic liquid(IL)provides a greener way to efficiently capture NH_(3).This paper provides rigorous process simulation,opt... 详细信息
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Local Characteristics Preservation Based State Identification in Oil-gas-water Three-phase Flow process  41
Local Characteristics Preservation Based State Identificatio...
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第41届中国控制会议
作者: Zhao Li Shumei Zhang Feng Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University
Oil-gas-water three-phase flow process is a dynamic non-stationary system,and the flow states are extremely complicated due to the three-phase *** at state identification of water-based dispersed three-phase flow,a st... 详细信息
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Multi-agent Deep Reinforcement Learning for Microgrid Energy Scheduling  41
Multi-agent Deep Reinforcement Learning for Microgrid Energy...
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第41届中国控制会议
作者: Zhiqiang Zuo Zhi Li Yijing Wang Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information EngineeringTianjin University
In this paper,we study the energy scheduling problem of solar-powered aircraft microgrid with multi-agent deep reinforcement learning algorithm under a centralized training and decentralized execution *** problem is m... 详细信息
来源: 评论
Two-phase Flow Pattern Diagnosis Based on Chaotic Recursive Graph and Spectral Analysis  41
Two-phase Flow Pattern Diagnosis Based on Chaotic Recursive ...
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第41届中国控制会议
作者: Ziqi Cui Chao Tan Hanrui Zhang Xuewei Shi Feng Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information EngineeringTianjin University
It is difficult to accurately measure the flow parameters of gas-liquid two-phase flow in horizontal pipe because of its complexity and *** of two-phase flow pattern is helpful to analyze fluid flow state and provide ... 详细信息
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Consensus of One-Sided Lipschitz Multi-Agent Systems with Input Saturation and Disturbance over Directed Graph  41
Consensus of One-Sided Lipschitz Multi-Agent Systems with In...
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第41届中国控制会议
作者: Zhiqiang Zuo Jiewen Ji Yijing Wang Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information EngineeringTianjin University
This paper investigates the consensus of one-sided Lipschitz(OSL) multi-agent systems(MASs) in the presence of input saturation and external disturbance over directed communication topology.A saturation avoidance stra... 详细信息
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Gas-water Two-phase Flow Status Monitoring based on CA-KCVA Method  41
Gas-water Two-phase Flow Status Monitoring based on CA-KCVA ...
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第41届中国控制会议
作者: Wentao Wu Chao Tan Shumei Zhang Feng Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University
Gas-water two-phase flow process is complex and ***-time monitoring of flow status evolution is helpful to the safe *** progress of multi-sensor technology makes it possible to accurately measure the flow information,... 详细信息
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