检索结果-内蒙古大学图书馆

Solo Adaptation for Distributed Synchronization With Application to Event-Triggered Linear Multi-Agent systems

IEEE Transactions on Automatic Control 2025年第6期70卷 4225-4232页

作者： Chen, Ci Zheng, Zhiyang Lewis, Frank L. Xie, Kan Xie, Shengli Guangdong University of Technology Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education School of Automation Guangzhou510006 China Guangdong University of Technology School of Automation Guangdong Guangzhou510006 China The University of Texas at Arlington UTA Research Institute Fort Worth76118 United States Guangdong University of Technology 111 Center for Intelligent Batch Manufacturing Based on IoT Technology School of Automation Guangzhou China Guangdong University of Technology Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing Ministry of Education School of Automation Guangzhou510006 China

We study a solo adaptation-based protocol design problem for distributed synchronization of event-triggered linear multi-agent systems (MAS) over general directed graphs. We show that a solo adaptive gain, a locally static control gain matrix, and a distributed state measurement are sufficient for obtaining adaptive distributed synchronization of linear MAS over directed graphs without any prior knowledge of the global communication network. We then extend the solo adaptation structure to formulate an event-triggered synchronization control protocol. The main feature of our result is that the time for triggering a subsequent event is now computed using the distributed event-triggered state measurement, rather than the continuous-time state measurement. © 1963-2012 IEEE.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

Fast resistivity imaging of transient electromagnetic using an extreme learning machine

引用

Soft Computing 2025年第2期29卷 1121-1131页

作者： Li, Ruiyou Zhang, Yong Li, Guang Li, Ruiheng Hu, Jia Li, Min School of Software and Internet of Things Engineering Jiangxi University of Finance and Economics NanChang330013 China School of Geophysics and Measurement Control Technology East China University of Technology NanChang330013 China School of Information Engineering Hubei University of Economics Wuhan430205 China The State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing400044 China

The transient electromagnetic method (TEM) is widely used in geophysical exploration. In TEM data interpretation, nonlinear inversion plays an important role. However, traditional TEM nonlinear inversion adopts the OCCAM imaging method, which merely presents the approximate shape of the stratum model, with poor inversion accuracy and much iteration time. To solve the above problems, a novel nonlinear inversion approach based on extreme learning machine (ELM) is proposed in this paper. The ELM is required to establish the input–output mapping relationship of the inversion network only once through the analytical method, which is different from the traditional neural network method that demands iterative gradient learning and is prone to fall into the local optimum. Moreover, the ELM inversion network by randomly assigning the hidden layer parameters is capable of mapping the observed TEM data and quickly producing resistivity images, which avoids time-consuming iteration and inversion calculations. The presented approach is applied to both synthetic and field examples. The results show that compared with the traditional nonlinear inversion algorithms (BP and OCCAM), the proposed method achieves better inversion accuracy and significantly reduces the calculation time, which verifies the effectiveness of the ELM algorithm for TEM data interpretation. Additionally, the research provides a new method and technology for TEM data inversion. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Electromagnetic transients

来源：评论

学校读者我要写书评

暂无评论

Temporal-Spatial Scheduling of Energy and Computation Resources for Charging and Computing Service Vehicles

引用

IEEE internet of things Journal 2025年

作者： Rong, Shichu Deng, Xiongtian Zhong, Weifeng Huang, Xumin Kang, Jiawen Xie, Shengli Yuen, Chau Guangdong University of Technology School of Automation Key Laboratory of Intelligent Detection and Manufacturing Internet of Things Ministry of Education Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Guangzhou510006 China Guangdong University of Technology School of Automation 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangdong-Hong Kong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China Nanyang Technological University School of Electrical and Electronic Engineering Singapore639798 Singapore

The growing adoption of electric vehicles (EVs) and expansion of internet-of-things (IoT) in-vehicle applications enhance vehicle intelligence and connectivity but also drive higher demand for both charging and computing services. Charging and Computing Stations (CCSs), integrating bidirectional chargers and edge computing servers and allowing optimal joint energy-computation management, has been taken as an effective solution to address this demand. This paper introduces a new concept called charging and computing service vehicle (CCSV) fleets, which are equipped with high-capacity batteries and edge servers, serving as mobile resources to support the stationary CCSs at different locations in a wide area. We propose a two-timescale model integrating temporal-spatial scheduling, charging/discharging management, and computation task offloading of the CCSV fleets. Our goal is to minimize the total system cost by optimizing the energy-computation coordination between the mobile CCSV fleets and the stationary CCSs. We construct an extended time-space network (TSN) with congestion nodes, providing a clearer depiction of the time-varying congestion conditions in the traffic network. For practical implementation, we develop a heuristic based on the convex-concave procedure (CCP) and penalty alternating direction method (PADM) to solve the problem quickly. Simulation results in a traffic network based on Guangzhou city demonstrate that the proposed model effectively leverages the mobility and multi-dimensional resources of the CCSV fleets to reduce the system cost significantly. © 2014 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Research on wireless sensor privacy data measurement and classification model based on IoT technology

引用

International Journal of Information and Communication technology 2023年第2期22卷 185-198页

作者： Wang, Jianye Zhuang, Chunsheng Liu, Xin Wu, Shunli Wang, Ding An, Haoping Institute of Applied Physics Henan Academy of Sciences Zhengzhou450008 China Henan Key Laboratory of Sensing Technology and System for Internet of Things Zhengzhou450008 China Henan Automation Engineering and Technology Research Centre Zhengzhou450008 China

Traditional wireless sensor privacy data measurement and classification process has the problems of low accuracy and very time-consuming. A new wireless sensor privacy data measurement and classification model is proposed. The measurement module of the model establishes two levels of privacy measurement elements from three dimensions, calculates the weight of level privacy elements by using Shannon information entropy, and obtains the privacy quantity of each data privacy measurement element in the data set. With the help of internet of things technology, the privacy data measurement and classification model of wireless sensor is designed. The experimental results show that the misjudgement rate of this model is very low, less than 5%, and the misjudgement error is kept below 10%. Using this model to protect the wireless sensor privacy data, the data running cost and time cost show a low level, has a certain application value. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Data privacy

来源：评论

学校读者我要写书评

暂无评论

A Survey on Deep Learning in Crop Planting 2

A Survey on Deep Learning in Crop Planting

引用

2nd International Symposium on Application of Materials Science and Energy Materials, SAMSE 2018

作者： Yang, Xiaofen Sun, Ming College of Information and Electrical Engineering China Agricultural University Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education Key Laboratory of Agricultural Information Acquisition Technology Ministry of Agriculture Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture Beijing100083 China

In recent years, with the explosive growth of data, deep learning has become one of the hottest research areas in artificial intelligence. Deep learning has been widely used in many fields such as medical field, industry, transportation system, agriculture is no exception. Crop planting is a vital part of agriculture. Here, we review deep learning applications in crop planting. In addition, we discuss the challenges and future trend of deep learning in crop planting. We hope that this review could promote more researchers to apply deep learning methods in crop planting field. © Published under licence by IOP Publishing Ltd.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

Intelligent Crop Planting Management and Quality Traceability system 2

Intelligent Crop Planting Management and Quality Traceabilit...

引用

2nd International Symposium on Application of Materials Science and Energy Materials, SAMSE 2018

Aiming at the farmland management problems, soil heavy metal pollutions problems and the agricultural product quality security problems, the system develops a link planting, acquisition, processing, logistics and distribution each link of intelligent crop planting management and achieves quality tracing based centralized service data gateway. This system extracts the information in real time from crop planting to agricultural product sales. It is conducive to the implementation of scientific planting and the sustainable development of agriculture, and it enables consumers to trace the quality of agricultural products. The main work of this research is as follow. The first is the construction of crop planting information management subsystem. It contains the information about field information, seeding, fertilizing, irrigation, weeding, pest controlling, spraying insecticide and harvest. The second is the construction of crop planting environmental monitoring subsystem based on sensor technology. It contains real-time environmental information in the process of crop growth, such as soil temperature and humidity, air temperatures and humidity, light intensity and video information, and it realizes remote monitoring of crops. The third is agricultural product quality traceability subsystem oriented to consumers. © 2019 Institute of Physics Publishing. All rights reserved.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

Control Policy Learning Design for Vehicle Urban Positioning via BeiDou Navigation

引用

Journal of systems Science & Complexity 2024年第1期37卷 114-135页

作者： QIN Yahang ZHANG Chengye CHEN Ci XIE Shengli LEWIS Frank L School of Automation Guangdong University of TechnologyGuangzhou 510006China Guangdong Key Laboratory of IoT Information Technology Guangzhou 510006China. Center for Intelligent Batch Manufacturing Based on IoT Technology Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou 510006China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China. UTA Research Institute The University of Texas at ArlingtonFort WorthTX 76019USA

This paper presents a learning-based control policy design for point-to-point vehicle positioning in the urban environment via BeiDou *** navigating in urban canyons,the multipath effect is a kind of interference that causes the navigation signal to drift and thus imposes severe impacts on vehicle localization due to the reflection and diffraction of the BeiDou ***,the authors formulated the navigation control system with unknown vehicle dynamics into an optimal control-seeking problem through a linear discrete-time system,and the point-to-point localization control is modeled and handled by leveraging off-policy reinforcement learning for feedback *** proposed learning-based design guarantees optimality with prescribed performance and also stabilizes the closed-loop navigation system,without the full knowledge of the vehicle *** is seen that the proposed method can withstand the impact of the multipath effect while satisfying the prescribed convergence rate.A case study demonstrates that the proposed algorithms effectively drive the vehicle to a desired setpoint under the multipath effect introduced by actual experiments of BeiDou navigation in the urban environment.

关键词： BeiDou navigation multipath effect prescribed convergence rate reinforcement learning urban localization.

来源：评论

学校读者我要写书评

暂无评论

A Fuzzy Clustering Algorithm Based on Multipath Component Trajectory for Millimeter Wave Radio Channels

引用

China Communications 2022年第11期19卷 99-111页

作者： Fei Du Yu Zhang Qingliang Li Xinyue Zhang Bo Zhu Zihao Fu Suiyan Geng Xiongwen Zhao State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical and Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China Hebei Key Laboratory of Power Internet of Things Technology North China Electric Power UniversityBaoding 071003HebeiChina National Key Laboratory of Electromagnetic Environment China Research Institute of Radiowave PropagationQingdao 266107China

Time-varying channel modeling plays an important role for many applications in time-variant scenarios,while most clustering algorithms focus on static channels and cannot accurately model the channel time-evolution *** this paper,a fuzzy clustering algorithm based on multipath component(MPC)trajectory is ***,both the distance and velocity similarities of the MPCs in different snapshots are taken into account to track the MPC trajectory,in which the fuzzy scheme and a kernel function are used to calculate the distance and velocity similarities,***,a fuzzy MPC trajectory clustering algorithm is proposed to cluster the MPCs in multiple *** MPCs in a snapshot are clustered according to the membership,which is defined as the probability that a MPC belongs to different ***,time-varying channels at 28 GHz are simulated to validate the performance of our proposed *** results show that our proposed algorithm is able to accurately identify the clusters in time-varying channels compared with the existing clustering algorithms.

关键词： channel modeling time-varying clustering multiple path component MPC trajectory 6G

来源：评论

学校读者我要写书评

暂无评论

Planning of distributed renewable energy systems under uncertainty based on statistical machine learning

引用

Protection and Control of Modern Power systems 2022年第1期7卷 619-645页

作者： Xueqian Fu Xianping Wu Chunyu Zhang Shaoqian Fan Nian Liu College of Information and Electrical Engineering China Agricultural University100083 BeijingChina Beijing Engineering and Technology Research Center for Internet of Things in Agriculture BeijingPeople’s Republic of China State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power University102206 BeijingChina

The development of distributed renewable energy,such as photovoltaic power and wind power generation,makes the energy system cleaner,and is of great significance in reducing carbon ***,weather can affect distributed renewable energy power generation,and the uncertainty of output brings challenges to uncertainty planning for distributed renewable *** systems with high penetration of distributed renewable energy involve the high-dimensional,nonlinear dynamics of large-scale complex systems,and the optimal solution of the uncertainty model is a difficult *** the perspective of statistical machine learning,the theory of planning of distributed renewable energy systems under uncertainty is reviewed and some key technologies are put forward for applying advanced artificial intelligence to distributed renewable power uncertainty planning.

关键词： Distributed renewable energy systems Statistical machine learning Uncertainty planning Renewable energy network

来源：评论

学校读者我要写书评

暂无评论

A location prediction based data gathering protocol for wireless sensor networks using a mobile sink 13

A location prediction based data gathering protocol for wire...

引用

13th International Conference on Ad-hoc Networks and Wireless, ADHOC-NOW 2014 accompanied by 2nd International Workshop on Emerging Technologies for Smart Devices, ETSD 2014, 2nd International Workshop on Marine Sensors and systems, MARSS 2014, Multimedia Wireless ad hoc Networks, MWaoN 2014, Security in Ad Hoc Networks, SecAN 2014, 2nd Smart Sensor Protocols and Algorithms, SSPA 2014 and 8th International Workshop on Wireless Sensor, Actuator and Robot Networks, WiSARN 2014

作者： Zhu, Chuan Wang, Yao Han, Guangjie Rodrigues, Joel J.P.C Guo, Hui College of Internet of Things Engineering Hohai University Changzhou China Guangdong University of Petrochemical Technology Maoming China Changzhou Key Laboratory of Photovoltaic System Integration and Production Equipment Technology Changzhou China Instituto de Telecomunicações University of Beira Interior Covilha Portugal

ISBN: (纸本)9783662463376

Traditional data gathering protocols in wireless sensor networks are mainly based on static sink, and data are routed in a multi-hop manner towards sink. In this paper, we proposed a location predictable data gathering protocol with a mobile sink. A sink’s location prediction principle based on loose time synchronization is introduced. By calculating the mobile sink location information, every source node in the network is able to route data packets timely to the mobile sink through multi-hop relay. This study also suggests a dwelling time dynamic adjustment method, which takes the situation that different areas may generate different amount of data into account, resulting in a balanced energy consumption among nodes. Simulation results show that our data gathering protocol enables data routing with less data transmitting time delay and balance energy consumption among nodes. © Springer-Verlag Berlin Heidelberg 2015.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：