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检索条件"机构=Advanced Control Systems Laboratory Control and Intelligent Processing Center of Excellence"
322 条 记 录,以下是51-60 订阅
排序:
Robust trajectory tracking for underactuated mechanical systems without velocity measurements
arXiv
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arXiv 2023年
作者: Javanmardi, N. Borja, P. Yazdanpanah, M.J. Scherpen, J.M.A. Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen Netherlands School of Engineering Computing and Mathematics University of Plymouth Plymouth United Kingdom Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran
In this paper, the notion of contraction is used to solve the trajectory-tracking problem for a class of mechanical systems. Additionally, we propose a dynamic extension to remove velocity measurements from the contro... 详细信息
来源: 评论
Fog Images Generation About Unmanned Surface Vessels with Improved Generative Adversarial Network
Fog Images Generation About Unmanned Surface Vessels with Im...
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Chinese control Conference (CCC)
作者: Yifeng Tang Zhihui Huang Chuancong Tang Chuanshang Luo Yifan Xu Bin Liu Hai-Tao Zhang Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation the Engineering Research Center of Autonomous Intelligent Unmanned Systems Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan China
This paper proposes a fog weather data augmentation method for the unmanned surface vessels (USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided ...
来源: 评论
Impulsive Formation control of Nonlinear Leader-Following Multi-agent systems with Input Saturation*
Impulsive Formation Control of Nonlinear Leader-Following Mu...
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Industrial Cyber-Physical systems (ICPS)
作者: Ni Zhang Xiaowei Jiang Xianhe Zhang Le You School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China School of Electrical Engineering and Automation Hubei Normal University Huangshi China
Leader-following formation analysis problem for a second-order nonlinear multi-agent system(MAS) with input saturation is investigated in this paper. And the impulsive formation control algorithm is introduced in the ... 详细信息
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Distributed formation control of networked mechanical systems
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IFAC-PapersOnLine 2022年 第13期55卷 294-299页
作者: N. Javanmardi P. Borja M.J. Yazdanpanah J.M.A. Scherpen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Cognitive Robotics Delft University of Technology Delft The Netherlands Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen The Netherlands
This paper investigates a distributed formation tracking control law for large-scale networks of mechanical systems. In particular, the formation network is represented by a directed communication graph with leaders a... 详细信息
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Distributed Optimal Load Frequency control with Stochastic Wind Power Generation
Distributed Optimal Load Frequency Control with Stochastic W...
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2021 European control Conference, ECC 2021
作者: Silani, Amirreza Cucuzzella, Michele Scherpen, Jacquelien M. A. Javad Yazdanpanah, Mohammad University of Groningen Jan C. Willems Center For Systems and Control ENTEG Faculty of Science and Engineering Groningen Netherlands University of Tehran Control Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Tehran Iran Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy
Motivated by the inadequacy of conventional control methods for power networks with a large share of renewable generation, in this paper we study the (stochastic) passivity property of wind turbines based on the Doubl... 详细信息
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A Novel Hybrid Model for Online Prediction of Rate of Penetration (ROP) in Drilling Process
A Novel Hybrid Model for Online Prediction of Rate of Penetr...
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Chinese Automation Congress (CAC)
作者: Yao Wang Chao Gan Weihua Cao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China
In this paper, a novel hybrid model is proposed for online prediction of rate of penetration (ROP) in drilling process, which including two parts (online data pre-processing and online hybrid modeling). In the first p...
来源: 评论
Incomplete Multi-view Clustering for Single cell RNA Sequencing Data
Incomplete Multi-view Clustering for Single cell RNA Sequenc...
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2021 China Automation Congress, CAC 2021
作者: Zhu, Tijian Zhu, Yuan Zhang, Chuan-Ke School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China
With the rapid development of sequencing technology, researchers can obtain a large number of single cell RNA sequencing (scRNA-seq) data which is useful for analysis of cell fate decision and growth process at indivi... 详细信息
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Reinforcement Learning with Reward Shaping and Hybrid Exploration in Sparse Reward Scenes
Reinforcement Learning with Reward Shaping and Hybrid Explor...
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Industrial Cyber-Physical systems (ICPS)
作者: Yulong Yang Weihua Cao Linwei Guo Chao Gan Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China
High precision modeling in industrial systems is difficult and costly. Model-free intelligent control methods, represented by reinforcement learning, have been applied in industrial systems broadly. The hard evaluated... 详细信息
来源: 评论
Template Matching and Trend Feature Analysis-Based Data Pre-processing Method for Seismic Wave Detection
Template Matching and Trend Feature Analysis-Based Data Pre-...
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Chinese Automation Congress (CAC)
作者: Zheng Xu Chao Gan Weihua Cao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China
In this paper, a template matching and trend feature analysis-based data pre-processing method for seismic wave detection is proposed with two stages. In the first stage, it involves extracting the rock physical param...
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Recurrent Attentional Reinforcement Learning for Fault Diagnosis of Hydraulic System
Recurrent Attentional Reinforcement Learning for Fault Diagn...
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International Conference on control, Decision and Information Technologies (CoDIT)
作者: Zhenhui Tang Ru Liu Kang Lou Chaojian Gao Jingcheng Wang SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya China Department of Automation Shanghai Jiao Tong University Shanghai China Shanghai Marine Equipment Research Institute Shanghai China Department of Automation the Key Laboratory of System Control and Information Processing Ministry of Education of China and the Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University Xi'an China
Recognizing fault types of machinery system is a fundamental but challenging task in industrial application. Although data-driven fault diagnosis method attains remarkable progress by learning fault features automatic... 详细信息
来源: 评论