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Control Policy Learning Design for Vehicle Urban Positioning via BeiDou Navigation

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.

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

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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

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

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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

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Fast resistivity imaging of transient electromagnetic using an extreme learning machine

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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

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Discovering periodic frequent travel patterns of individual metro passengers considering different time granularities and station attributes

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International Journal of Transportation Science and technology 2024年第2期14卷 12-26页

作者： Zhibin Jiang Yan Tang Jinjing Gu Zhiqing Zhang Wei Liu College of Transportation Engineering Tongji UniversityShanghai 201804China The Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji UniversityShanghai 201804China Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety Tongji UniversityShanghai 201804China School of Information Science and Engineering Yunnan UniversityKunming 650500China The Key Laboratory of Internet of Things Technology and Application in Yunnan Province Kunming 650500China Technical Center of Shanghai Shentong Metro Group Co. Ltd.Shanghai 201103China

Periodic frequent pattern discovery is a non-trivial task to discover frequent patterns based on user interests using a periodicity *** conventional algorithms for periodic frequent pattern detection have numerous applications,there is still little research on periodic frequent pattern detection of individual passengers in the *** travel behavior of individual passengers has complex spatio-temporal characteristics in the metro network,which may pose new challenges in discovering periodic frequent patterns of individual metro passengers and developing mining algorithms based on real-world smart card *** study addresses these issues by proposing a novel pattern for metro passenger travel pattern called periodic frequent passenger traffic patterns with time granularities and station attributes(PFPTS).This discovered pattern can automatically capture the features of the temporal dimension(morning and evening peak hours,week)and the spatial dimension(entering and leaving stations).The corresponding complete mining algorithm with the PFPTS-tree structure has been *** evaluate the performance of PFPTS-tree,several experiments are conducted on one-year real-world smart card data collected by an automatic fare collection system in a certain large metro *** results show that PFPTS-Tree is efficient and can discover numerous interesting periodic frequent patterns of metro passengers in the real-world dataset.

关键词： Metro passenger travel pattern Spatio-temporal characteristics Periodic frequent pattern PFPTS-tree structure Smart card data

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Flexible linear clock-based distributed self-triggered active power-sharing secondary control of AC microgrids

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Global Energy Interconnection 2024年第6期7卷 786-797页

作者： Yulin Chen Xing Huang Guangxin Zhi Shaohua Yang Hongxun Hui Donglian Qi Yunfeng Yan Fengkai Gao Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012P.R.China Hainan Institute Zhejiang UniversitySanya572000P.R.China College of Electrical Engineering Zhejiang UniversityHangzhou310027P.R.China State Key Laboratory of Internet of Things for Smart City University of MacaoMacao999078P.R.China

Traditional active power sharing in microgrids,achieved by the distributed average consensus,requires each controller to continuously trigger and communicate with each other,which is a wasteful use of the limited computation and communication resources of the secondary *** enhance the efficiency of secondary control,we developed a novel distributed self-triggered active power-sharing control strategy by introducing the signum function and a flexible linear *** continuous communication–based controllers,the proposed self-triggered distributed controller prompts distributed generators to perform control actions and share information with their neighbors only at specific time instants monitored by the linear ***,this approach results in a significant reduction in both the computation and communication ***,this design naturally avoids Zeno ***,a modified triggering condition was established to achieve further reductions in computation and *** simulation results confirmed that the proposed control scheme achieves distributed active power sharing with very few controller triggers,thereby substantially enhancing the efficacy of secondary control in MGs.

关键词： Active power sharing Distributed secondary control Self-triggered mechanism AC microgrid Control efficiency

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Energy-Efficient UAV Trajectory Plan for 6G Networks 1

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11th International Conference on Communications, Signal Processing, and systems, CSPS 2022

作者： Qin, Peng Wu, Xue Zhao, Xiongwen Zhao, Honghao State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical and Electronic Engineering North China Electric Power University Beijing102206 China Hebei Key Laboratory of Power Internet of Things Technology North China Electric Power University Baoding071003 China

ISBN: (数字)9789819912605

ISBN: (纸本)9789819912599

Leveraging UAVs for access and Altitude Platform Stations (HAPSs) for data backhaul to construct the Air-Ground Integrated Network (AGIN) is a feasible solution to achieve seamless network coverage for remote IoT devices in future 6G era. However, the limited battery of IoT terminals and constrained onboard energy storage of UAVs make system energy-efficiency becomes a new concern. To cope with the challenge, we propose a C-NOMA AGIN model for remote area. Then, we investigate the UAV trajectory plan problem for maximizing system energy efficiency (EE). We provide the solution to obtain the near-optimal UAV trajectory and flight speed. Results prove that the proposed approach is superior to others in terms of EE. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Energy efficiency

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

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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

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

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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

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Small-size temperature/high-pressure integrated sensor via flip-chip method

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Microsystems & Nanoengineering 2024年第4期10卷 153-162页

作者： Mimi Huang Xiaoyu Wu Libo Zhao Xiangguang Han Yong Xia Yi Gao Zeyu Cui Cheng Zhang Xiaokai Yang Zhixia Qiao Zhikang Li Feng Han Ping Yang Zhuangde Jiang State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong UniversityXi’an 710049China Xi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and System Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China School of Mechanical Engineering Xi’an Jiaotong University710049 Xi’anChina School of Instrument Science and Technology Xi’an Jiaotong University710049 Xi’anChina Chongqing Key Laboratory of Micro-Nano Systems and Intelligent Sensing Chongqing Academician WorkstationChongqing 2011 Collaborative Innovation Center of Micro/Nano Sensing and Intelligent Ecological Internet of ThingsChongqing Technology and Business UniversityNan’an DistrictChongqing 400067China Xi’an Aerospace Yuanzheng Fluid Control Co.Ltd. Xi’an 710049China

Hydraulic technology with smaller sizes and higher reliability trends,including fault prediction and intelligent control,requires high-performance temperature and pressure-integrated *** designs rely on planar wafer-or chip-level integration,which is limited by pressure range,chip size,and low *** propose a small-size temperature/high-pressure integrated sensor via the flip-chip *** pressure and temperature units are arranged vertically,and the sensing signals of the two units are integrated into one plane through silicon vias and gold–gold bonding,reducing the lateral size and improving the efficiency of signal *** flip-chip technique ensures a reliable electrical connection.A square diaphragm with rounded corners is designed and optimised with simulation to sense high pressure based on the piezoresistive *** temperature sensing unit with a thin-film platinum resistor measures temperature and provides back-end high-precision compensation,which will improve the precision of the pressure *** integrated chip is fabricated by MEMS technology and packaged to fabricate the extremely small integrated *** integrated sensor is characterised,and the pressure sensor exhibits a sensitivity and sensitivity drift of 7.97mV/MPa and−0.19%FS in the range of 0–20 MPa and−40 to 120℃.The linearity,hysteresis,repeatability,accuracy,basic error,and zero-time drift are 0.16%FS,0.04%FS,0.06%FS,0.18%FS,±0.23%FS and 0.04%FS,*** measurement error of the temperature sensor and temperature coefficient of resistance is less than±1°C and 3142.997 ppm/℃,*** integrated sensor has broad applicability in fault diagnosis and safety monitoring of high-end equipment such as automobile detection,industrial equipment,and oil drilling platforms.

关键词： size corners sizes

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