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30th IEEE International Conference on Parallel and Distributed systems, ICPADS 2024

作者： Cheng, Long He, Haoyang Gu, Yan Liu, Qingzhi Zhao, Zhiming Fang, Fang North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering Beijing China Wageningen University and Research Information Technology Group Netherlands University of Amsterdam Research Group of Multi-Scale Networked Systems Netherlands

ISBN: (纸本)9798331515966

Scheduling workflows in hybrid cloud environments presents significant challenges due to the inherent complexity of workflows and the dynamic nature of cloud resources. This complexity is further increased when attempting to balance workflow performance with privacy protection. Recent efforts have leveraged deep reinforcement learning (DRL) to address these challenges. However, most of these approaches rely on single-agent models, which can lead to security issues and scalability problems due to their centralized processing. Specifically, the properties of workflows are transferred to the single agent, which risks leaking privacy information. Our paper addresses these issues by introducing MARS, a real-time workflow scheduling method that prioritizes privacy protection in hybrid clouds. MARS leverages multi-agent deep reinforcement learning (MADRL) to optimize the workflow scheduling of cloud virtual machines (VMs). The benefit of our solution is that it relies on the collaborative learning of multi-agents on multiple VMs, which could assign user data to specific cloud servers for privacy protection while sharing training experiences between agents. In our implementation, MARS aims to reduce workflow completion time and operational costs while complying with strict privacy protection guidelines. The experimental results demonstrate that MARS can significantly surpass existing methods, reducing makespan by an average of 53.18% and costs by 61.98% compared to basic techniques, and achieving 20.26% and 25.71% improvements over the latest advanced methods, respectively. © 2024 IEEE.

关键词： Deep reinforcement learning

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear systems Against Actuator Faults

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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International Symposium on Autonomous systems (ISAS)

作者： Shanlin Liu Yingwei Zhang Xudong Zhao Hesheng Wang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of IntelligentControl and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent.

关键词： Actuators Backstepping Fault tolerant systems process control Artificial neural networks control systems Approximation error

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Resilient Distributed Quadrotor UAVs Game: Addressing FDI and Physical Attacks

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IEEE Transactions on Vehicular Technology 2025年

作者： Geng, Mei-Jie Ding, Hua-Feng Yao, Xiang-Yu Lv, Maolong China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan430074 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Air Force Engineering University College of Air Traffic Control and Navigation Xi'an710038 China

Distributed quadrotor unmanned aerial vehicles (UAVs) are increasingly deployed in critical applications, including reconnaissance, disaster response, and transportation, where system resilience is paramount. However, their complex dynamics and reliance on cyber-physical systems make them highly vulnerable to adversities such as uncertain dynamics, time-varying input disturbances, false data injection (FDI), and physical attacks. This paper proposes a hierarchical framework consisting of a game layer and an execution layer to enhance the resilience of a noncooperative game involving distributed UAVs. In the game layer, a novel FDI observer mitigates communication and computational FDI attacks, facilitating convergence to infinitesimal ranges around the Nash equilibrium (NE) point. The execution layer addresses uncertain dynamics and physical attacks, ensuring that UAVs can track a narrow neighborhood of the NE even in the presence of actuator failures. Extensive simulations validate the algorithm's effectiveness and robustness against mixed attack scenarios, underscoring its potential for real-world UAV applications. © 1967-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Polarized Modulation for RIS-Aided Vehicular Communication Networks

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IEEE Internet of Things Journal 2025年第12期12卷 18616-18627页

作者： Shang, Pingping Xie, Longhui Li, Jun Feng, Li Hai, Han Xu, Binbin Li, Jie Yu, Ling Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China Hubei University of Technology Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430068 China Guangzhou University Research Center of Intelligent Communication Engineering School of Electronics and Communication Engineering Guangzhou510006 China Key Laboratory of On-Chip Communication and Sensor Chip of Guangdong Higher Education Institutes Guangzhou510006 China Donghua University School of Information Science and Technology Shanghai201620 China Maritime Communication Research Institute Wuhan430068 China Guangdong Provincial Hospital of Chinese Medicine Guangzhou510120 China State Key Laboratory of Traditional Chinese Medicine Syndrome Guangzhou510120 China

The reconfigurable intelligent surface (RIS) stands as an emergent technique poised to revolutionize future vehicular communication. In order to facilitate the application of RIS in vehicular communication, this paper proposes two effective RIS-aided schemes tailored for polarization modulation (PM) aiming to achieve remarkable spectral efficiency. Specifically, Scheme I proposes a novel index modulation (IM) aided PM-RIS framework that innovatively encodes information across three distinct dimensions, the indices of dual-polarized antennas (DP-AEs), PM symbols and the reflecting surface indices of the RIS. Scheme II employs a deep neural network method to analyze the channel state information (CSI) for transmit antenna selection, that enhances the reliability and interference immunity in dynamic conditions while reducing computational complexity. Furthermore, a stepwise estimation (SE) method is introduced at the detection stage, which significantly reduces the complexity associated with information decoding. The simulation results highlight the superiority of the proposed system. Compared with traditional PM systems, it demonstrates enhanced performance in terms of spectral efficiency, channel stability, and bit error rate (BER). © 2014 IEEE.

关键词： Signal modulation

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The Enhancing Effect of the East Asian Subtropical Westerly Jet on Summer Extreme High-Temperature Events over Central-Eastern China Since the Late 1990s

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Advances in Atmospheric Sciences 2025年第3期42卷 453-466页

作者： Chujie GAO Yuyu NIU Gen LI Shanlei SUN Bo LU Chaofan LI Bei XU Jinglong HUANG Xiubao SUN College of Oceanography&Key Laboratory of Marine Hazards Forecasting Ministry of Natural ResourcesHohai UniversityNanjing 210098China Key Laboratory of Meteorological Disaster Ministry of Education(KLME)&Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China Laboratory for Climate Studies and CMA-NJU Joint Laboratory for Climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China Xiong’an Institute of Meteorological Artificial Intellegence Xiong'an 071708China Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of the Chinese Academy of SciencesBeijing 100049China College of Intelligent Science and Control Engineering Jinling Institute of TechnologyNanjing 211169China

The increase in frequency and intensity of Extreme High-temperature Events(EHEs)over Central-Eastern China(CEC)in recent decades has severely impacted social development and *** observation and reanalysis datasets,this study explores the effect of the East Asian subtropical westerly jet stream(EAJ)on the CEC EHEs for the summers spanning 1979–*** its general relative location to the right side of the upper-level jet stream exit region,CEC would theoretically suffer more EHEs with a stronger and northwardly-shifted EAJ in summer due to the likelihood of abnormal subsidence induced by the ***,such an EAJ–EHE connection has been unstable over the past four decades but has displayed an evident interdecadal *** the late 1990s,the interannual variation of the EAJ was manifested mainly by its meridional displacement in the northeastern part of East Asia;thus,the atmospheric responses were essentially located to the east of CEC,exerting less of an influence on the CEC ***,since the late 1990s,the EAJ variation has featured an intensity change in its center over the northwest portion of the CEC,which has resulted in a westward shift in atmospheric responses to cover the CEC ***,the EAJ could potentially affect the summer CEC EHEs during 2000–*** findings offer support for an in-depth understanding of the formation mechanisms of extreme weather/climate events of this nature and thus provide a scientific reference for seasonal climate predictions.

关键词： summer extreme high-temperature events East Asian subtropical jet atmospheric circulation central-eastern China interdecadal change

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Lightweight LiDAR-Camera 3D Dynamic Object Detection and Multi-Class Trajectory Prediction

arXiv

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arXiv 2025年

作者： He, Yushen Zhao, Lei Deng, Tianchen Fang, Zipeng Chen, Weidong Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

Service mobile robots are often required to avoid dynamic objects while performing their tasks, but they usually have only limited computational resources. So we present a lightweight multi-modal framework for 3D object detection and trajectory prediction. Our system synergistically integrates LiDAR and camera inputs to achieve real-time perception of pedestrians, vehicles, and riders in 3D space. The framework proposes two novel modules: 1) a Cross-Modal Deformable Transformer (CMDT) for object detection with high accuracy and acceptable amount of computation, and 2) a Reference Trajectory-based Multi-Class Transformer (RTMCT) for efficient and diverse trajectory prediction of mult-class objects with flexible trajectory lengths. Evaluations on the CODa benchmark demonstrate superior performance over existing methods across detection (+2.03% in mAP) and trajectory prediction (-0.408m in minADE5 of pedestrians) metrics. Remarkably, the system exhibits exceptional deployability - when implemented on a wheelchair robot with an entry-level NVIDIA 3060 GPU, it achieves realtime inference at 13.2 fps. To facilitate reproducibility and practical deployment, we release the related code of the method at https://***/TossherO/3D Perception and its ROS inference version at https://***/TossherO/ros packages. Copyright © 2025, The Authors. All rights reserved.

关键词： Mobile robots

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An Anti-Time Domain Impulse Interference Algorithm for Aviation Swarms Communication system

An Anti-Time Domain Impulse Interference Algorithm for Aviat...

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2022 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2022

作者： Shang, Yaobo Zhang, Dongwei Li, Zhe Liang, Xiaolong Ren, Baoxiang Air Force Engineering University Air Traffic Control and Navigation College Xi'an710051 China Shaanxi Key Laboratory of Meta-Synthesis for Electronic and Information System Xi'an710051 China

ISBN: (数字)9781665499910

ISBN: (纸本)9781665499910

Aiming at the problem of anti-impulse interference in aviation swarms communication system, a time-domain anti-impulse interference algorithm combining nonlinear filtering and interleaving coding is proposed. Firstly, the mathematical model of time-domain impulse interference is established by Middleton Class A model, and then the model is analyzed, and the signal processing methods such as limiting method, punching method and other nonlinear filtering methods are integrated, and the simplified method of channel measurement is obtained. Aiming at the problem of continuous errors caused by continuous pulse interference, a method combining channel coding and outer interleaving is proposed. This method turns continuous errors into random errors through interleaving and deinterleaving, and then uses channel decoding to complete information error correction. Through the analysis and numerical simulation of the demodulation performance of this algorithm, it is proved that it can significantly improve the anti-interference performance of aviation swarms communication system, and it is easy to realize and has good application value. © 2022 IEEE.

关键词： Error correction

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Non-Line-Of-Sight Target Localization in T-Shaped Roadways Using Simo Fmcw Millimeter-Wave Radar

SSRN

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SSRN 2024年

作者： Hu, Qingsong Luo, Yujia Wang, Liudi Cheng, Yuanxun Zhang, Yuansheng Yuan, Shuya Kou, Zhihao School of Information and Control Engineering China University of Mining & Technology Jiangsu Xuzhou221116 China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process Beijing100032 China Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing100032 China

The hazardous and complex nature of underground mining imposes stringent safety requirements on autonomous driving. T-shaped roadways, common in such environments, present significant challenges for non-line-of-sight (NLOS) target localization. Traditional underground positioning technologies often fail in these settings due to severe signal attenuation and multipath effects, leading to potential accidents. This manuscript proposes a novel localization algorithm using single-input-multi-output (SIMO) Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar to address these challenges. We analyze millimeter wave multipath propagation in T-shaped tunnels and construct an FMCW multipath echo model. Using CA-CAFAR and MVDR algorithms, we accurately estimate target distance and angle information. Additionally, a theoretical false point matching elimination method is designed to improve positioning accuracy by mitigating false target interference. Field tests in typical T-shaped NLOS scenarios demonstrate the method's high-precision positioning, enhancing the safety and efficiency of autonomous vehicles in coal mines. © 2024, The Authors. All rights reserved.

关键词： Coal mines

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A novel two-stage Dissolved Gas Analysis fault diagnosis system based semi-supervised learning

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High Voltage 2022年第4期7卷 676-691页

作者： Xuemin Tan Chao Guo Ke Wang Fu Wan College of Control Engineering Chengdu University of Information TechnologyChengduChina State Grid Chengdu Power Supply Company ChengduChina China Electric Power Research Institute BeijingChina State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina

Dissolved Gas Analysis(DGA)is an important method for oil-immersed transformer fault ***,collecting labelled DGA data is difficult because the determi-nation of the transformer fault is time-consuming and expensive in the transformer substation,but DGA data without labels is easier to ***,the paper pro-posed a semi-supervised two-stage diagnostic system based DGA by using less labelled *** two-stage system includes a novel semi-supervised feature selection based Genetic Algorithm(GA)and Support Vector Machine(SVM)model(SSL-FS-GASVM)for selecting optimal features and a novel semi-supervised transformer fault diagnosis model based improved Artificial Fish Swarm Algorithm(AFSA)and SVM(SSL-IAFSA-SVM)for optimising the SVM ***,the performances of SSL-FS-GASVM and SSL-IAFSA-SVM models are tested and compared with traditional supervised diagnostic models combined with other optimisation methods,*** results show that the proposed two-stage system works in optimising features and parameters and has strong robustness in solving small sample classification problems.

关键词： fault diagnosis system

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Cyber topology design guaranteed structural controllability for networked systems

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Science China(information Sciences) 2022年第11期65卷 303-304页

作者： Jianbin MU Shaoyuan LI Jing WU Ning LI Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University

Dear editor,Structure analysis is of crucial importance for achieving reliable system functionality. In many real-world systems, the exact parameters of system model are not available owing to modeling uncertainties or measurement noise, and then structural controllability is pursued in control configuration design. As first proposed by Lin in [1],

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