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第三十八届中国控制会议

作者： Shengnan Tian Min Wu Luefeng Chen Jinhua She Manli Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

ISBN: (纸本)9781728123295;9789881563972

This paper concerns robust stabilization for a class of nonlinear systems with uncertainties and disturbaces. The equivalent-input-disturbance(EID) approach is utilized to estimate the influence of nonlinearities and exogenous disturbances on the output of the system. A robust stability condition is derived in terms of linear matrix inequalities. Moreover, two parameters are used to tune the robustness of the system. Simulation results show that it is more effective to stabilize the system using the developed method than using the sliding-mode control(SMC) method.

关键词： Robust stabilization equivalent-input-disturbance nonlinear uncertain system disturbance linear matrix inequality(LMI)

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Application of digital lock-in amplifier in complex electromagnetic interference of substation

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Progress In Electromagnetics Research C 2020年 106卷 105-120页

作者： Song, Jiabing Song, Hengli Yang, Xuan Dong, Haobin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

There is complex electromagnetic interference in the substation. In order to improve detection accuracy, a digital lock-in amplifier is used in the detection of the grounding grid. This paper introduces the principle of non-destructive testing of grounding grid based on electromagnetic method. Firstly, the distribution characteristics of surface magnetic induction intensity at different frequencies are obtained by CDEGS simulation. At the same time, it describes the principle and structure of an orthogonal vector type digital lock-in amplifier in detail. In order to realize the high-precision grounding grid detection system, the hardware circuit of the digital lock-in amplifier is designed by FPGA and analog-to-digital converter. The digital lock-in amplifier algorithm is implemented in the FPGA. Finally, the digital lock-in amplifier is tested. The test results show that when the signal-to-noise ratio of the signal to be tested is −20 dB, the signal amplitude measurement error is less than 3%. The designed digital lock-in amplifier is applied to the actual grounding grid detection, and the topology and corrosion of the grounding network can be detected. Therefore, the digital lock-in amplifier can be effectively applied to non-destructive testing of grounding grid. © 2020, Electromagnetics Academy. All rights reserved.

关键词： Signal interference

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A Novel Coiled Cable-Conduit-Driven Hyper-Redundant Manipulator for Remote Operating in Narrow Spaces

A Novel Coiled Cable-Conduit-Driven Hyper-Redundant Manipula...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Mingrui Luo Yunong Tian En Li Minghao Chen Cunfeng Kang Guodong Yang Min Tan School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Engineering Laboratory of Industrial Vision and Intelligent Equipment Technology Chinese Academy of Sciences Beijing China Beijing-University of Technology Beijing China

Operating in narrow spaces is an important challenge in the development of robots. Redundant manipulators are one way to solve this problem, but their mechanism design and control method still have much room for improvement. In this paper, we propose a coiled cable-conduit-driven hyper-redundant manipulator (C-CDHRM) with great slenderness and flexibility. In terms of mechanism design, it considers both compactness and operability. By imitating the structure and behavior of a constricting snake, it can be uncoiled sequentially from a coiled storage state, led by the head. In terms of control methods, we propose a multi-layer control system that can make remote operations more accurate and reliable. On the one hand, guiding, segmenting, and following the path overcome the planning ambiguity caused by redundancy. On the other hand, conduit transmission modeling and cable length correction overcome the nonlinear mapping of cable-driven joints and were verified in experiments. Through tests, the mobile integrated system composed of C-CDHRM has an excellent performance in operation precision and accuracy, ensuring safety and accessibility in narrow spaces. Finally, in field experiments, the inspection and cleaning of various types of electrical equipment have been successfully completed, showing excellent application prospects.

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Learning Greenhouse Climate control Policy from Monitored Data

Learning Greenhouse Climate Control Policy from Monitored Da...

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2022 Chinese automation Congress, CAC 2022

作者： Zhao, Xiaoxuan Wang, Haoyu Wang, Xiujuan Lewlomphaisarl, Udom Li, Dong Hua, Jing Kang, Mengzhen The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technologies Beijing China National Electronics and Computer Technology Center Pathum Thani Thailand Institute of Digital Agriculture Zhejiang Academy of Agricultural Sciences Hangzhou China Qingdao AgriTech Co. Ltd. Qingdao China

ISBN: (纸本)9781665465335

The knowledge of solar greenhouse growers on environment control plays an important role in greenhouse production and management. We proposed a way to extract the control strategies from the monitored data of greenhouses by building a long short-term memory (LSTM) model. The result is verified according to the real monitored data of a solar greenhouse, which shows that the model can learn the control strategy of a ventilator in the solar greenhouse. Through monitored data and models, the knowledge of greenhouse ventilation control can be learned, and automatic control can be achieved in a greenhouse with a similar configuration. © 2022 IEEE.

关键词： Greenhouses

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Energy Efficiency Optimization for Full-Duplex D2D Communications Underlaying Distributed Antenna systems

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年

作者： Liu, Zhan Liao, Zhiyuan Li, Chunquan Zhang, Zhijun Yu, Junzhi Liu, P.X. Hunan University of Humanities Science and Technology School of Information Loudi417000 China Nanchang University School of Information Engineering Nanchang330031 China Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction Nanchang330031 China South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

In this paper, we investigate the total system energy efficiency (EE) of full-duplex (FD) device-to-device (D2D) communications underlaying distributed antenna systems (DAS), where remote access units (RAUs), D2D users (DUs), and cellular users (CUs) are all capable of FD operation. Specifically, we jointly optimize subcarrier assignment and power allocation under the quality of service (QoS) requirements of CUs and DUs and the maximum power constraints of RAUs, CUs, and DUs. In addition, we propose a novel spectrum sharing strategy that allows each subcarrier to be assigned to multiple CUs and/or multiple D2D pairs (DPs) for flexibility. To solve the formulated non-convex optimization problem, we first employ fractional programming to transform the objective function in the optimization problem from the fractional form into the equivalent subtractive form. Then, an efficient iterative resource allocation algorithm is proposed, which needs to solve an inner problem in each iteration. After relaxing the variables and introducing penalty factors, the non-convex inner problem is transformed into a convex problem through the successive convex approximation (SCA) method and solved by iterative algorithm. Simulation results demonstrate that the proposed algorithm can considerably improve the system EE compared to other benchmark schemes. Furthermore, the proposed spectrum sharing strategy is superior to the existing sharing strategies. © 2017 IEEE.

关键词： Convex optimization

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An oracle bone recognition method based on eigenvalue-based preprocessing and deep learning

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Signal, Image and Video Processing 2025年第8期19卷

作者： Zhou, Chun-Yang Liu, Zhen-Tao Lumo Road Hubei Wuhan430074 China Lumo Road Hubei Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Lumo Road Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Lumo Road Hubei Wuhan430074 China

Recognition of oracle bone characters is essential for accurately interpreting Chinese cultural history. However, existing recognition techniques are significantly challenged by severe noise present in the original images, leading to low recognition accuracy. To address this issue, this paper proposes an oracle bone recognition method based on eigenvalue-based preprocessing and deep learning. The preprocessing method computes four tailored eigenvalues-equivalent connectivity domain diameter, minimum connectivity domain distance, point feature analysis matrix, and point eigenvalue-based on the unique structural characteristics of oracle bone characters, enabling more effective noise reduction. Subsequently, an improved model, DC-YOLOv8, is introduced, which replaces the standard convolution module with a deformable convolution module in the high-level layers of the backbone to enhance adaptability to highly deformed characters. Additionally, the Convolutional Block Attention Module is incorporated into the head component to improve the model’s ability to extract key features in critical regions. Experimental results demonstrate that YOLOv8 achieves accuracy rates of 90.14% and 90.97% on two datasets after applying the proposed preprocessing method. Furthermore, the accuracy of DC-YOLOv8 reaches 95.11%, 91.74%, and 93.75% across three datasets. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Feature Selection

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Large, complex, and Realistic Safety Clothing and Helmet Detection: Dataset and Method

arXiv

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arXiv 2023年

作者： Yu, Fusheng Li, Jiang Wang, Xiaoping Wu, Shaojin Zhang, Junjie Zeng, Zhigang The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China The Hubei Key Laboratory of Brain-Inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China The Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Detecting safety clothing and helmets is paramount for ensuring the safety of construction workers. However, the development of deep learning models in this domain has been impeded by the scarcity of high-quality datasets. In this study, we construct a large, complex, and realistic safety clothing and helmet detection (SFCHD) dataset. SFCHD is derived from two authentic chemical plants, comprising 12,373 images, 7 categories, and 50,552 annotations. We partition the SFCHD dataset into training and testing sets with a ratio of 4:1 and validate its utility by applying several classic object detection algorithms. Furthermore, drawing inspiration from spatial and channel attention mechanisms, we design a spatial and channel attention-based low-light enhancement (SCALE) module. SCALE is a plug-and-play component with a high degree of flexibility. Extensive evaluations of the SCALE module on both the ExDark and SFCHD datasets have empirically demonstrated its efficacy in enhancing the performance of detectors under low-light conditions. The dataset and code are publicly available at https://***/lijfrankopen/SFCHD-SCALE. Copyright © 2023, The Authors. All rights reserved.

关键词： Chemical plants

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Social manufacturing pattern in the intelligent reform of the shoes and clothing industry 1

Social manufacturing pattern in the intelligent reform of th...

引用

1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Cao, Yansong Wang, Yutong Dai, Juwu Zhu, Xihao Wang, Fei-Yue Macau Institute of Systems Engineering Macau University of Science and Technology China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Ningbo Sanbody Intelligent Technology Co. LTD Ningbo China University of Nottingham Faculty of Science and Engineering Ningbo China

ISBN: (纸本)9781665433372

Along with economic globalization, the shoes and clothing market is undergoing huge changes and is facing increasing individualized demands. To realize personalized customization, we propose a social manufacturing pattern for the shoes and clothing industry. On the customer side, we collect costumer information with the help of 3D scanning and virtual fitting. On the production side, we replace human labor with intelligent production equipment. On the enterprise management side, we construct a cloud platform to realize source maximization. Through this social manufacturing pattern, we expect to accelerate the intelligent reform of the shoes and clothing industry. © 2021 IEEE.

关键词： Shoe manufacture

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PV Maximum Power-point Tracking Using Modified Particle Swarm Optimization under Partial Shading Conditions

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Chinese Journal of Electrical Engineering 2020年第4期6卷 106-121页

作者： Al-wesabi Ibrahim M.B.Shafik Min Ding Mohammad Abu Sarhan Zhijian Fang Ahmed.G.Alareqi Tariq Al’moqri Ayman.M.Al-Rassas School of Automation China University of GeoscienceWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China School of Oil and Natural Gas Engineering China University of GeosciencesWuhan 430074China School of Mathematics and Physics China University of GeoscienceWuhan 430074China School of Petroleum Engineering China University of PetroleumEast ChinaQingdao 266580China

A novel maximum power-point tracking approach is proposed based on studies investigating the output characteristics of photovoltaic(PV)systems under partial shading *** existence of partially shaded conditions leads to the presence of several peaks on PV curves,which decrease the efficiency of conventional ***,the proposed algorithm,which is based on the modified particle-swarm optimization(MPSO)technique,increases the output power of PV systems under such abnormal conditions and has a better performance compared to other *** proposed method is examined under several scenarios for partial shading condition and non-uniform irradiation levels using Matlab,and to investigate its effectiveness adequately,the results of the proposed method are compared with those of the neural network *** experimental results show that the proposed method can decrease the interference of the local maximum power-point to cause the PV system to operate at a global maximum *** efficiency of the MPSO is achieved with the least number of steady-state oscillations under partial shading conditions compared with the neural network method.

关键词： Photovoltaic(PV) maximum power point tracking(MPPT) step-up converter artificial neural networks(ANNs) particle-swarm optimization(PSO)

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NeRF in Robotics: A Survey

arXiv

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arXiv 2024年

作者： Wang, Guangming Pan, Lei Peng, Songyou Liu, Shaohui Xu, Chenfeng Miao, Yanzi Zhan, Wei Tomizuka, Masayoshi Pollefeys, Marc Wang, Hesheng The University of Cambridge ETH Zurich Switzerland The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China ETH Zurich Zurich Switzerland Mechanical Systems Control Laboratory University of California Berkeley United States

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable numerous capabilities. Among these, the Neural Radiance Field (NeRF) has sparked a trend because of the huge representational advantages, such as simplified mathematical models, compact environment storage, and continuous scene representations. Apart from computer vision, NeRF has also shown tremendous potential in the field of robotics. Thus, we create this survey to provide a comprehensive understanding of NeRF in the field of robotics. By exploring the advantages and limitations of NeRF, as well as its current applications and future potential, we hope to shed light on this promising area of research. Our survey is divided into two main sections: The Application of NeRF in Robotics and The Advance of NeRF in Robotics, from the perspective of how NeRF enters the field of robotics. In the first section, we introduce and analyze some works that have been or could be used in the field of robotics from the perception and interaction perspectives. In the second section, we show some works related to improving NeRF's own properties, which are essential for deploying NeRF in the field of robotics. In the discussion section of the review, we summarize the existing challenges and provide some valuable future research directions for reference. © 2024, CC BY-NC-ND.

关键词： Robotics

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