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Computing Challenges of UAV Networks: A Comprehensive Survey

computers, Materials & Continua 2024年第11期81卷 1999-2051页

作者： Altaf Hussain Shuaiyong Li Tariq Hussain Xianxuan Lin Farman Ali Ahmad Ali AlZubi School of Computer Science&Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqing400065China School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhou310018China School of Artificial Intelligence Nanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science and Engineering School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063Republic of Korea Department of Computer Science Community CollegeKing Saud UniversityRiyadh11495Saudi Arabia

Devices and networks constantly upgrade,leading to rapid technological ***-dimensional(3D)point cloud transmission plays a crucial role in aerial computing terminology,facilitating information *** network types,including sensor networks and 5G mobile networks,support this ***,Flying Ad hoc Networks(FANETs)utilize Unmanned Aerial Vehicles(UAVs)as nodes,operating in a 3D environment with Six Degrees of Freedom(6DoF).This study comprehensively surveys UAV networks,focusing on models for Light Detection and Ranging(LiDAR)3D point cloud compression/*** topics covered include autonomous navigation,challenges in video streaming infrastructure,motivations for Quality of Experience(QoE)enhancement,and avenues for future ***,the paper conducts an extensive review of UAVs,encompassing current wireless technologies,applications across various sectors,routing protocols,design considerations,security measures,blockchain applications in UAVs,contributions to healthcare systems,and integration with the Internet of Things(IoT),Artificial Intelligence(AI),Machine Learning(ML),and Deep Learning(DL).Furthermore,the paper thoroughly discusses the core contributions of LiDAR 3D point clouds in UAV systems and their future prediction along with mobility *** also explores the prospects of UAV systems and presents state-of-the-art solutions.

关键词： Autonomous vehicles UAV systems UAV transmission UAV in healthcare future of UAV system security measures

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Fault Tolerant control for the Vibration Displacement System of a Continuous Casting Mold Based on a Fault Detection Observer

Fault Tolerant Control for the Vibration Displacement System...

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第43届中国控制会议

作者： Wenqi Hao Yiming Fang Le Liu Xiaonan Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Engineering Research Center of the Education Ministry for Intelligent Control System and Intelligent Equipment Yanshan University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In this paper,a fault detection observer and an adaptive sliding mode fault-tolerant controller are designed for the vibration displacement system of a continuous casting mold with actuator faults and load torque ***,a mathematical model of a continuous casting mold vibration displacement system driven by a servo motor with actuator faults and load disturbance uncertainties are ***,a fault detection observer is designed to obtain information on actuator faults,load disturbances,and system state ***,based on the information from the fault detection observer,an adaptive sliding mode fault-tolerant controller is designed,and the stability of the designed system is proved using Lyapunov stability ***,the effectiveness of the designed adaptive sliding mode fault-tolerant controller based on fault observer is verified through simulation.

关键词： Continuous casting mold Fault detection observer Fault tolerant control Actuator fault Vibration displacement system Driven by a servo motor

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A traffic signal control method based on improved deep reinforcement learning

A traffic signal control method based on improved deep reinf...

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2024 China Automation Congress, CAC 2024

作者： Bao-Lin, Ye Dong, Chen Peng, Wu Weimin, Wu Li, Lingxi Bin, Chen School of Information Science and Engineering Jiaxing University Jiaxing China School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette United States Jiaxing Key Laboratory of Smart Transportations Jiaxing University Jiaxing China

ISBN: (纸本)9798350368604

In order to solve the problem that the existing traffic signal control methods usually need to predefine the phase sequence or phase duration, a single intersection traffic signal control method based on improved deep reinforcement learning Double DQN (DDQN) was proposed. Firstly, a traffic signal control model based on deep reinforcement learning DDQN was constructed to optimize the estimated value of action-value function and the iterative process of target value. Secondly, the original one-dimensional action space was discretized into a three-dimensional action space composed of phase selection, phase duration and loss factor, and the next phase and phase green time to be executed were intelligently decided. Finally, a new loss function is designed based on the loss factor, which can dynamically adjust the loss weight of different actions according to the difference of importance. The simulation test is carried out based on the microscopic simulation platform SUMO. The experimental results show that, compared with the baseline method, the proposed method reduces the average waiting time by 28.1%, the average queue length by 29.7%, and the average number of parking vehicles by 18.8%. © 2024 IEEE.

关键词： Deep reinforcement learning

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Hierarchical Energy Management Strategy of Hybrid Electric Truck Fleet under Connected Environment

Hierarchical Energy Management Strategy of Hybrid Electric T...

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第43届中国控制会议

作者： Qizhe Lu Wenbin Tang Zitong Pang Yahui Zhang Xiaohong Jiao School of Electrical Engineering Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University School of Mechanical Engineering Yanshan University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Considering the slow-moving and energy-consuming issues that tend to occur when truck fleets drive,this paper proposes a hierarchical energy management strategy(EMS) for the hybrid electrical truck(HET) fleet,including speed planning and energy *** speed threshold range that allows the whole fleet to pass through the traffic light is computed in the upper-layer speed *** the model predictive control framework,a multi-objective optimization function is constructed for speed planning to find the optimum *** the lower-layer energy management,an offline model is established for power allocation between the Integrated Starter Generator and the Electric Motor and gear shift selection of automated manual transmission to reduce the dimensionality of the control ***,an adaptive equivalent consumption minimum strategy(A-ECMS) is designed based on the fleet's optimal speed *** the offline part,the transformation relationship between the co-state and equivalence factor is established based on Pontryagin's minimum principle(PMP),and PMP obtains the globally optimal control sequence in the historical driving cycle to train a back-propagation neural network(BPNN).The BPNN model predicts the current optimal co-state in the online part,transformed into a real-time optimal equivalence factor to guide the A-ECMS online *** simulation results indicate that the fuel economy of the proposed EMS is comparable to that of the global optimization method PMP and superior to that of Fixed EF-ECMS and ***,it enables the HET fleet to pass through traffic lights without stopping,thereby ensuring queue continuity and improving the passage efficiency of the fleet.

关键词： hybrid electric trucks equivalent consumption minimization strategy fleet speed planning back-propagation neural network model predictive control

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A switching-based backstepping sliding mode control for space manipulator in presence of gravity variation

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High Technology Letters 2021年第4期27卷 454-462页

作者： Liu Fucai Zhao Wenna Meng Lingcong Liu Shuo Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004P.R.China Engineering Department University of SheffieldSheffieldUK

A novel switching-based backstepping sliding mode control(SBSMC) scheme is devised for the space manipulator exposed to different *** a view to distinct differences in dynamics properties when the operating conclition of space manipulator changer,the space manipulator can be thought of as a system composed of two subsystems,the ground subsystem and the space *** different types of backstepping sliding mode(BSM) controllers are designed,one is suited for the ground subsystem and the other is for the space *** switching between two subsystems can be implemented automatically when the switching mechanism is triggered,and the controllers for their subsystems experience synchronous *** this way,the space manipulator always has good behaviors in trajectory ***,multi-Lyapunov functions are introduced to prove the stability of this switching *** to simulation results,the method constructed in this research has better performance in control precision and adaptability compared with proportional-derivative(PD) control.

关键词： space manipulator microgravity switching system multi-Lyapunov functions backstepping sliding mode control(BSMC)

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G-Anomaly: A Pyramid Graph Transformer-based Vision-Language Model for General industrial Anomaly Detection

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IEEE Transactions on Automation Science and engineering 2025年

作者： Li, Jiaqi Wen, Shuhuan Fang, Bin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Beiing University of Posts and Telecommunications Department of Artificial intelligence Beijing China

Visual-language alignment is crucial for enhancing the domain adaptability of industrial anomaly detection models. However, the existing methods overlook the importance of structured image representation, fail to further distinguish topological differences between anomalies and the inherent textures of products, which reduces the accuracy of semantic matching. To address this problem, we propose a novel industrial anomaly detection model G-Anomaly, to preserve the topological structure of the sample images and further enhance the model’s domain adaptability. We designed Pyramid Graph Transformer as a visual encoder to extract multi-scale visual features, which can directly preserve the structural relationships between different regions of the image, and also optimize the over-smoothing issue present in deep graph networks, thereby retaining the distinguishability of anomalous nodes. Additionally, we design a Multi-level Domain Adapter that ensures semantic consistency of anomalous features across different scales and contexts by performing visual-language matching at various resolutions and levels of abstraction. This enhances the model’s domain adaptability for anomaly detection for a wide range of industrial products. We collect and craft an actual solar panel dataset PV_actual AD, and conduct extensive experiments on the public dataset MVTec AD as well as the actual solar panel dataset PV_actual AD. This has demonstrated that G-Anomaly not only performs well in standard testing environments but also exhibits robustness and domain adaptability for anomaly detection tasks in real-world scenarios. © 2025 IEEE. All rights reserved.

关键词： Semantics

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ENABLING HIGH SENSITIVITY AIRFLOW MEASUREMENT USING PHASE-CHANGE MATERIALS 26

ENABLING HIGH SENSITIVITY AIRFLOW MEASUREMENT USING PHASE-CH...

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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Zhou, Yushan Cao, Yunqi Sepúlveda, Nelson Zhang, Hongjian State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou310027 China Department of Electrical and Computer Engineering Michigan State University East LansingMI48824 United States

ISBN: (纸本)9781733419048

A lab-on-a-chip (LOC) thermal mass flow sensor based on microelectromechanical systems (MEMS) technology is designed, fabricated, and characterized. Vanadium dioxide (VO2), a nonlinear phase-change material with 3-order of change in resistance is placed in the down streaming direction of the heat source as the sensing element. The resistance of VO2 is monitored under gas flow rates ranging from 0 to 37.8 μL·s-1 with a maximum sensitivity of 368.56 ppm/(μL·min-1). The studies presented in this research may enable the application of utilizing nonlinear metamaterial in microfluidic LOC sensors with orders of magnitude improvement in sensitivity. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Phase change materials

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A Novel A-ESO Composited Non-recursive control Methodology for Complex High-order Disturbed Nonlinear Systems

A Novel A-ESO Composited Non-recursive Control Methodology f...

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第42届中国控制会议

作者： Cong Zhang Shiji Liu Shuang Liu School of Electrical Engineering Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

This paper mainly focuses on a disturbance rejection control methodology for a series of mismatched and matched disturbed complex ***,a novel finite-time arbitrary-order extended state observer(A-ESO) is proposed to accurately estimate the system states,disturbances,and their corresponding order *** then,a novel concise non-recursive control ideology utilizing all the estimations of A-ESO is proposed to strictly guarantee finite-time stability and convergence of the whole closed-loop ***,compared with the existing non-recursive control methods,the essential characteristic is that all the estimation information is utilized to construct the composite *** will be tremendously conducive to cost-saving and promoting practical implementations.

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Event-Triggered Robust Model Predictive control for Multi-Agent Systems Under Hybrid Attacks

Event-Triggered Robust Model Predictive Control for Multi-Ag...

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第42届中国控制会议

作者： Yongxin Yin Jianxiong Li Chongyi Gao Yiming Fang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Department of Electromechanical Engineering Tangshan University

In this paper,the consensus control problem for multi-agent systems（MASs） suffering hybrid attacks is discussed,in which the hybrid attacks include randomly occurring deception attacks on system dynamic behavior and denial-of-service attacks（DoS）.An event-triggered robust model predictive control（RMPC） method is presented to achieve the consensus of MASs under hybrid *** can be proved that the consensus errors can be asymptotic with prescribed H performance,the sufficient condition for stability can be given in terms of linear matrix inequalities（LMIs）,and the controller gains are obtained by solving an optimization problem involving some *** the event-triggered mechanism with maximum trigger interval,not only can not only save computation time and facilitate the efficiency of the shared resources but also can effectively be responsible for the negative impact of cyber-attacks on system ***,simulation results are given to illustrate the validity and effectiveness of the proposed method.

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Tactile-Based Object Pose Estimation Employing Extended Kalman Filter 8

Tactile-Based Object Pose Estimation Employing Extended Kalm...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Lin, Qiguang Yan, Chaojie Li, Qiang Ling, Yonggen Zheng, Yu Lee, Wangwei Wan, Zhaoliang Huang, Bidan Liu, Xiaofeng College of IoT Engineering Hohai University Jiangsu Key Laboratory of Special Robotic Technology Jiangsu Changzhou213022 China Zhejiang University Institute of Cyber-System and Control State Key Laboratory of Industrial Control and Technology Hangzhou China Bielefeld33619 Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350300178

In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the estimation of the object's pose using an Extended Kalman Filter (EKF) based approach. We defined and derived the state and measurement equations, as well as evaluated the estimation accuracy in grasping tasks. The approach is able to effectively account for the pose transition caused by tactile pushing, and the mapping from the object's pose to the contact position and normal direction as measured by the tactile sensor. The method was evaluated in multiple grasping experiments in simulation scenarios. Results show that the estimation can converge towards the ground truth in a relatively short period of time, with displacement and rotation errors remaining within acceptable levels. This new method has the potential to improve the accuracy and reliability of robotic grasping and manipulation tasks. © 2023 IEEE.

关键词： Extended Kalman filters

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