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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Wen, Xiaojing Chen, Cailian Ren, Cheng Lyu, Ling Guan, Xinping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China Dalian Maritime University School of Information Science and Technology Dalian116026 China

ISBN: (纸本)9798350345384

Multiple types of sensors are utilized for remote monitoring of single industrial process to compensate for the limited accuracy of a single type of sensor. Network slicing technology is considered promising for collecting data from heterogeneous sensors and meeting diverse Quality of Service (QoS) requirements. However, existing research on network slicing optimization mainly focuses on inter-slice resource constraints based on slice heterogeneity, neglecting slice coupling feature. In this regard, this paper proposes a novel network slicing framework for edge-assisted industrial IoT systems. The framework includes a slice coupling model and network resource allocation (transmission and computing) to address the problem of improving estimation performance while ensuring system convergence. The slice coupling model is primarily composed of the estimation error covariance of two slices, calculated using the Age of Task (AoT) as a bridge, which reflects the accuracy and freshness of the estimation. To reduce the complexity of the direct solution, the optimization problem is scaled down and decoupled. The iterative Particle Swarm Optimization (PSO) algorithm is proposed to determine the allocation rates of inter-slice transmission and computing resources. Simulation results demonstrate that the proposed algorithm achieves a flexible balance under heterogeneous estimation weights and exhibits near-optimal performance. © 2023 IEEE.

关键词： Resource allocation

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Vision-Based Autonomous Landing of a Quadrotor UAV on a Double-Layered Nested Landing Marker

Vision-Based Autonomous Landing of a Quadrotor UAV on a Doub...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Mu, Lingxia Zhang, Yuan Xin, Jing Zhang, Youmin School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Department of Mechanical and Industrial Engineering Concordia University MontrealH3G 1M8 Canada

ISBN: (纸本)9789811966125

This paper focuses on the vision-based autonomous landing mission of a quadrotor unmanned aerial vehicle (UAV). A double-layered nested Aruco landing marker is designed which can adapt to the situation that the field of sight of airborne camera changes as the UAV’s altitude decreases during the landing. Then, considering that the landing marker might be obstructed in certain situation, traditional Aruco detection method cannot effectively recognize marker. A YOLOv4 deep learning algorithm is used for marker detection. In addition, to address the problem of false detection in some test results, normalized Wasserstein distance is used to replace the non-maximum suppression to deal with redundant frames. The UAV’s relative location to the marker is then calculated and landing mission is finally achieved by the image-based visual servoing strategy. The simulation on Gazebo demonstrates that the designed marker is effective for the UAV landing mission and the revised YOLOv4 detection algorithm can increase detection results accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Antennas

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Learning oriented cross-entropy approach to user association in load-balanced HetNet

arXiv

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arXiv 2018年

作者： Huang, Xietian Xu, Wei Xie, Guo Jin, Shi You, Xiaohu Southeast University Nanjing China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'An University of Technology Xi'an China

This letter considers optimizing user association in a heterogeneous network via utility maximization, which is a combinatorial optimization problem due to integer constraints. Different from existing solutions based on convex optimization, we alternatively propose a cross-entropy (CE)-based algorithm inspired by a sampling approach developed in machine learning. Adopting a probabilistic model, we first reformulate the original problem as a CE minimization problem which aims to learn the probability distribution of variables in the optimal association. An efficient solution by stochastic sampling is introduced to solve the learning problem. The integer constraint is directly handled by the proposed algorithm, which is robust to network deployment and algorithm parameter choices. Simulations verify that the proposed CE approach achieves near-optimal performance quite efficiently. Copyright © 2018, The Authors. All rights reserved.

关键词： Heterogeneous networks

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A UAV Path Planning Algorithm Based on an Improved D* Lite Algorithm for Forest Firefighting

A UAV Path Planning Algorithm Based on an Improved D* Lite A...

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Chinese Automation Congress (CAC)

作者： Zhaohui Luo Youmin Zhang Lingxia Mu Jing Huang Jing Xin Han Liu Shangbin Jiao Guo Xie Yingmin Yi Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China Concordia University Montreal Canada

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

This paper proposes a new type of forest firefighting method. When one or more suspected fire spots are found in the forest, the firefighting Unmanned Aerial Vehicles (UAVs) can safely and quickly reach the desired location, conduct a thorough investigation of the suspected fire spots. If a fire occurs, it is necessary to drop firefighting materials to put out the fire. At the same time, considering the characteristics of limited endurance and low load capability have always limited the applications of UAVs, Unmanned Ground Vehicles (UGVs) are considered in this paper as an additional and comprehensive problem solution to provide energy and supplement materials for UAVs. In order to enable firefighting UAV to plan a safe and effective path in real time in the complex forest environment, a new improved D*Lite algorithm is proposed for UAVs in the mission team. Even when the 3D workspace is partially known or completely unknown, the algorithm can plan an effective path so that the firefighting UAV can move to the fire spots and UGV in real time.

关键词： Path planning Heuristic algorithms Unmanned aerial vehicles Forestry Smoothing methods Real-time systems Planning

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Group Behaviour control Based on Aggregation and Dilation

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IFAC Proceedings Volumes 2008年第2期41卷 6072-6077页

作者： Bin Xin Jie Chen Li-Hua Dou Zhi-Hong Peng Department of Automatic Control School of Information Science and Technology Beijing Institute of Technology Beijing 100081 Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education China

The phenomenon of aggregation and dilation(A&D) widely exists in nature. The mechanism behind it is regarded as the effect of some kind of attraction and repulsion(A&R). A&R control becomes a popular and promising way of controlling the structure and distribution of a group composed of several and even numerous individuals. This paper presents the concepts of aggregation, dilation and group evolution criticality based on group variance. We investigate the relationship between different levels of A&D as a foundation for the introduction of A&D analysis. The applications of A&D analysis and A&R control in several researches, including population-based optimization and group behavior control about multi-agent, are given in the form of simulation experiments.

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Fixed-time extended state observer-based trajectory tracking control for autonomous underwater vehicles

Fixed-time extended state observer-based trajectory tracking...

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作者： Zheng, Jiaqi Song, Lei Liu, Lingya Yu, Wenbin Zhu, Shanying Wang, Yiyin Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

In this paper, we investigate the trajectory tracking control problem for autonomous underwater vehicles (AUVs) with time-varying external disturbances of currents and waves in the sea. To solve the problem, a fixed-time extended state observer (FTESO)-based tracking controller is proposed. Firstly, by using the extended state observer, the FTESO is proposed for estimating the external disturbances and the velocities of the AUV within the fixed convergence time. Based on the FTESO, the fixed-time controller is proposed for reducing the tracking errors and improving robustness performance. Theoretical analysis is given, which shows that the unknown external disturbances can be compensated and tracking error can converge to zero within the fixed time. Simulation results show that the proposed FTESO controller not only guarantees the fixed-time convergence but also reduces the trajectory tracking errors of the AUV. © 2021 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Autonomous underwater vehicles

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Surface Defect Detection Based on Deep Learning and Collaborative Cloud-edge Computation 7

Surface Defect Detection Based on Deep Learning and Collabor...

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7th International Conference on Computer and Communications, ICCC 2021

作者： He, Shunjie Yang, Bo Zhu, Dafeng Li, Cheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665409506

Surface defect detection is a fundamental step of quality management. Nowadays, surface defect detection system based on machine vision technology has made great progress which can gradually replace the human inspector. With the help of convolutional neural networks, the accuracy and stability of the surface defect detection algorithm are improving rapidly. However, it is difficult to process the images which have small defect areas and complex backgrounds. Furthermore, lacking defective samples and limited computation resources are also tough problems. To deal with these problems, a two-stage algorithm combined with object detection and classification networks is proposed. Transform learning and data augmentation are used to deal with the problem of lacking defect samples. Besides, a detection system based on collaborative cloud-edge computation is designed to improve the performance of the algorithm. The result shows that the proposed method has high performance and low requirements of computation resources. © 2021 IEEE.

关键词： Computer vision

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Adaptive Generalized Projective Synchronization of a New Fractional Chaotic system with uncertain parameters

Adaptive Generalized Projective Synchronization of a New Fra...

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第30届中国控制与决策会议

作者： Jiaoru Huang Kun Zhong Fucai Qian The International Joint Research Center of Autonomous Systems and Intelligent Control Xi'an Technological University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

This paper investigates the generalized projective synchronization scheme of a new fractional chaotic system, which can display a four-wing chaotic attractor when the order of system is in the range of 0.82 and ***, considering the situation with unknown parameters, an adaptive nonlinear controller is obtained for synchronization and parameters identification based on fractional-order Lyapunov stability theorem. The fractional-order adaptation law, which can update parameters estimation errors online, is derived to ensure the stability of synchronization error system. Numerical simulations are used to verify the results.

关键词： Four-wing chaotic attractors uncertain parameter generalized projective synchronization parameter identification

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A new method of single-phase ground fault line selection based on principal component analysis and support vector machine

A new method of single-phase ground fault line selection bas...

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Chinese Automation Congress (CAC)

作者： Sicheng Wen Shangbin Jiao Qing Zhang Qing Wang Key Laboratory of complex system and intelligent information processing in Shaanxi Province Xi'an University of Technology Xi’an China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

For the existing single-fault line selection methods that cannot accurately identify all single-phase grounding faults in a small current grounding system, this paper proposes a new method of small current single-phase grounding fault line selection based on the combination of principal component analysis and support vector machine. This method first uses wavelet transform to denoise and divide the transient zero-sequence current of the bus and each feeder; then uses the zero-sequence energy method to first detect the bus fault. If the detected fault is a bus fault, end of line selection; if the detected fault is not a bus fault, use principal component analysis to reduce the dimension of the fault zero sequence current signal. Select the three most influential factors, and enter the support vector machine classifier to finally get the fault line. Use Matlab/Simulink to build a simulation model and simulate fault experiments. The final experimental results show that this method has high stability in line selection and is not affected by noise, ground resistance, fault angle, fault distance, and the number of feeders. Identity bus faults and feeder faults, and select lines accurately.

关键词： OWL Germanium

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An edge-based model for non-Markovian sexually transmitted infections in coupled network

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International Journal of Biomathematics 2020年第2期13卷 119-153页

作者： Xiaofeng Luo Junyuan Yang Zhen Jin School of Computer and Information Technology Shanxi University Taiyuan 030006P.R.China Complex System Research Center Shanxi University Taiyuan 030006ShanxiP.R.China Shanxi Key Laboratory of Mathematical Techniques and Big DataAnalysis on Disease Control and Prevention Shanxi University Taiyuan 030006ShanxiP.R.China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Taiyuan 030006 P.R.China

In this paper,allowing for general transmission and recovery times distributions,we proposed an edge-based age-structured-like compartmental model for STIs(EBACMS)in a coupled *** considered sexual transmissions between men with also heterosexual ***,we gave the general approach of proving the nonnegativity of solutions for the system coupling ordinary and partial differen-tial equations,which can be applied to all edge-based compartment *** then analyzed the epidemic threshold Ro with different distributions which couples the thresholds of the single-layer and bipartite networks in the percolation *** also studied the global stability of disease-free equilibrium with R0<1 and the final epidemic size F(the proportion of the population experiencing infection during the epidemic)with R0>*** addition,numerical simulations indicated that given a fixed exponential transmission distribution,a higher variance(with same mean)in general recovery distribution gives smaller R0 and *** analysis on Ro and F in terms of the parameters illustrated that male-to-male transmission routes have a greater impact on Rg and F than the heterosexual transmission routes for the Markovian transmission process and arbitrary recovery *** results provide a good theoretical guideline to consider the distributions of real-world STIs.

关键词： Coupled network EBCM non-Markovian process sexually transmitted disease epidemic age-structured

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