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检索条件"任意字段=Conference on Internet Quality and Performance and Control of Network Systems"

共 10553 条记录，以下是311-320 订阅

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control Enhancement of Traction Electric Drives Using Neural network Predictive controller

Control Enhancement of Traction Electric Drives Using Neural...

引用

2024 International conference on control, Automation and Diagnosis, ICCAD 2024

作者： Cocogne, Romain Bilavarn, Sebastien Mokadem, Mostafa El Douzane, Khaled Silicon Mobility Sophia Antipolis France Université Côte d'Azur Cnrs Leat Sophia Antipolis France

ISBN: (纸本)9798350361025

This paper investigates the use of a hybrid Recurrent Neural network to reproduce the behavior of a nonlinear long-horizon Model Predictive controller (MPC) used in traction motor drive systems. The goal is to assess the operational validity and control performances of such neural network based predictive controller (further referred to as Full Neural network MPC), and to compare against Field Oriented control (FOC), the current industry standard. Based on simulation results using a Model in the Loop (MiL) environment, it is shown that the proposed FNN-MPC can properly learn the behavior and characteristics of the nonlinear long-horizon MPC while being more computationally implementable, with still better control performance and quality than FOC. © 2024 IEEE.

关键词： Recurrent neural networks

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Leveraging Symmetry in RL-based Legged Locomotion control

Leveraging Symmetry in RL-based Legged Locomotion Control

引用

2024 International conference on Intelligent Robots and systems

作者： Su, Zhi Huang, Xiaoyu Ordonez-Apraez, Daniel Li, Yunfei Li, Zhongyu Liao, Qiayuan Turrisi, Giulio Pontil, Massimiliano Semini, Claudio Wu, Yi Sreenath, Koushil Univ Calif Berkeley Uc Berkeley CA 94720 USA Tsinghua Univ Inst Interdisciplinary Informat Sci Beijing Peoples R China Ist Italiano Tecnol Genoa Italy Shanghai Qi Zhi Inst Shanghai Peoples R China

ISBN: (纸本)9798350377712;9798350377705

Model-free reinforcement learning is a promising approach for autonomously solving challenging robotics control problems, but faces exploration difficulty without information about the robot's morphology. The under-exploration of multiple modalities with symmetric states leads to behaviors that are often unnatural and sub-optimal. This issue becomes particularly pronounced in the context of robotic systems with morphological symmetries, such as legged robots for which the resulting asymmetric and aperiodic behaviors compromise performance, robustness, and transferability to real hardware. To mitigate this challenge, we can leverage symmetry to guide and improve the exploration in policy learning via equivariance / invariance constraints. We investigate the efficacy of two approaches to incorporate symmetry: modifying the network architectures to be strictly equivariant / invariant, and leveraging data augmentation to approximate equivariant / invariant actor-critics. We implement the methods on challenging loco-manipulation and bipedal locomotion tasks and compare with an unconstrained baseline. We find that the strictly equivariant policy consistently outperforms other methods in sample efficiency and task performance in simulation. Additionaly, symmetry-incorporated approaches exhibit better gait quality, higher robustness and can be deployed zero-shot to hardware.

关键词： Reinforcement learning

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Effective Capacity of internet of Underwater Things networks Enabled By Multi-Aperture UOWC

Effective Capacity of Internet of Underwater Things Networks...

引用

2024 IEEE Middle East conference on Communications and networking, MECOM 2024

作者： Rahman, Ziyaur Romdhane, Imene Hassan, Md. Zoheb Kaddoum, Georges MontréalQC Canada Université Laval QuébecQC Canada

ISBN: (纸本)9798350376715

internet of Underwater Things (IoUT) is the underwater network of connected objects and systems that have a wide range of applications, ranging from undersea critical infrastructure monitoring and marine biodiversity observation to underwater surveillance. Underwater optical wireless communication (UOWC) systems, which are characterized by large bandwidth and high data rate, are a key enabler of IoUT networks. However, oceanic turbulence and pointing error (PE) are essential performance limiting factors for enabling UOWC in IoUT networks. In this paper, we investigate the quality-of-service (QoS) performance of multi-aperture UOWC-based IoUT networks while adopting the mixture exponential-generalized gamma (EGG) distribution to jointly model the oceanic turbulence fading and PE. To this end, we derive a closed-form expression of the effective capacity (EC) from evaluating the system's maximum achievable data rate in the presence of EGG turbulence and PE subject to certain statistical delay constraints. Special cases of the EC for asymptotic high signal-to-noise ratio (SNR) regimes and loose statistical delay constraints are also analyzed. Through extensive simulations, we justify the validity of the derived EC expressions. Our numerical results also demonstrate that the multi-aperture technique improves EC in the EGC turbulence fading and PE channels, thereby supporting strict statistical delay constraints with a high data rate. © 2024 IEEE.

关键词： Underwater optical wireless communication

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internet of Things (IoT) based Battery Maintenance System 7

Internet of Things (IoT) based Battery Maintenance System

引用

7th International conference on Intelligent Computing and control systems, ICICCS 2023

作者： Asvika, D. Deepika, M. Selvabarkavi, M. Shalini, V. Baby Information Technology Kalasalingam Academy of Research and Education Krishnankoil India

ISBN: (纸本)9798350397253

Batteries, which are collections of electrochemical cells, produce electricity to run electrical equipment. Batteries continuously transform chemical energy into electrical energy, and for optimum performance, they need to be properly maintained using systems of management with particular monitoring capabilities. In order to avoid potential health, safety, and property risks associated with battery use, techniques including charge management systems and temperature regulation are implemented. These systems use merit-based metrics to control battery performance. In this work, neural network is used to keep track of the battery's health. The proposed system consists of a load cell, a temperature sensor, a voltage transformer, and a current transformer. It features automatic battery cleaning powered by servo motors. Also, alert for different battery fault conditions will be sent. © 2023 IEEE.

关键词： Electric loads

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Enhanced Active Power control Capability of Grid Coupled Solar PV System 34

Enhanced Active Power Control Capability of Grid Coupled Sol...

引用

34th Australasian Universities Power Engineering conference

作者： Faisal, M. Robinson, Duane A. Rahman, O. Univ Wollongong Australian Power Qual Res Ctr Wollongong NSW 2522 Australia

ISBN: (纸本)9798350377958;9798350377941

Grid-tied solar photovoltaic-based distributed generation systems are required to provide consistent and controlled levels of active and reactive power to the grid. However, the intermittent nature of the solar resource available to PV systems makes the use of energy storage system indispensable for enhancing balance of supply and demand and reliability. The PV inverter controller plays a pivotal role in ensuring the proportional percentage output of the active and reactive power, contributing to system stability. Most of the research in the literature focuses on the design and control of small-scale power converters to enhance performance, however, ongoing research persists regarding the practical integration of these converters onto the grid. Upon integration of the system with the grid, the voltages at the point of common coupling synchronize with those of the grid. This paper evaluates the potential of regulating the voltage level of grid coupled solar system and upholding the power quality within a medium voltage distribution network. The control of active and reactive power was achieved through manipulation of the dq-component of the grid current. No additional PI loop is used to regulate the DC-side voltage, which is another advantage of this configuration.

关键词： active power energy storage energy sharing inverter voltage control

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Precoding Schemes for Wireless Beam Modulation System 99

Precoding Schemes for Wireless Beam Modulation System

引用

IEEE 99th Vehicular Technology conference (VTC-Spring)

作者： Chen, Xiao Liu, Congxi Yu, Xinyan Long, Hang Beijing Univ Posts & Telecommun Wireless Signal Proc & Network Lab Key Lab Universal Wireless Commun Minist Educ Beijing Peoples R China

ISBN: (纸本)9798350387414

Millimeter wave communication systems offer a new perspective for addressing bandwidth congestion, but their high hardware cost and power consumption limit their application in internet of Things (IoT) devices. A wireless beam modulation (WBM) system has been proposed as a cost-effective alternative. The patch antenna array on the IoT nodes formulates two transmit beams with different directions. Information bits are transmitted through the energy difference of aligned beams by WBM. However, challenges arise from the random emission of beams and the avoidance of complex data processing, resulting in signal attenuation and reduced communication quality. In this paper, the optimal precoding scheme is first derived, and then we design a manifold optimization-based precoding scheme that directly handles the constant modulus constraint of the precoding vectors. Simulation results show that the proposed precoding scheme achieves a significant performance improvement over existing ones and performs close to the theoretical upper bound when the gains of the different paths in the channel are fairly consistent.

关键词： internet of Things millimeter wave wireless beam modulation beamforming precoding manifold optimization singular value decomposition

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BBR-SJ: Optimization of time delay jitter in GEO satellite network 24

BBR-SJ: Optimization of time delay jitter in GEO satellite n...

引用

3rd International conference on Signal Processing, Computer networks and Communications, SPCNC 2024

作者： Ren, Mingming Wang, Hongdong Huang, Cao Luo, Feiteng Xizang Minzu University Shaanxi Xianyang China Pervasive Communication Research Center Purple Mountain Laboratories Jiangsu Nanjing China

ISBN: (纸本)9798400710834

With the continuous advancement of communication technology, GEO (geostationary orbit) satellite has shown significant advantages in the field of long-distance communication, and will be an important part of the future satellite-earth converged communication architecture. In order to solve the problem of delay jitter in GEO satellite network using tcp protocol, we proposed BBR-SJ improvement protocol. BBR-SJ monitor the network time changes and dynamically adjust the transmission parameters, judging the degree of jitter based on the dispersion of delay data, and implementing corresponding rate control and congestion control strategy, effectively reduce the delay jitter on data transmission, and by extending the delay validity period detection window, reduce the error rate of the detection process. Simulation experiments show that BBR-SJ is excellent in reducing time delay jitter and improving transmission stability, effectively maintaining high-rate transmission and preventing network congestion, significantly enhancing the network performance, and providing a key technology for improving the service quality of satellite communication. © 2024 Copyright held by the owner/author(s).

关键词： Satellite communication systems

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Application of Multiclassification for Detecting Intrusions in IoT and Their Type Recognizing

Application of Multiclassification for Detecting Intrusions ...

引用

2024 International conference "quality Management, Transport and Information Security, Information Technologies", QM and TIS and IT 2024

作者： Malik, Niang Papa Sidorenko, Valentina G. Federal State Institution of Higher Education Russian University of Transport Control and Information Security Moscow Russia

ISBN: (纸本)9798350367522

The goal of the work is to identify the possibility of using machine learning algorithms with a multiclass approach to detect attacks in internet of Things (IoT) networks, determine their type, improve the security of IoT devices, protect devices and their users from attackers. The experimental results show that the proposed multi-layer gradient boosting classifier model can achieve better prediction of small classes without sacrificing the prediction performance of numerous classes, but requires much more time than other methods. The second algorithm that has good accuracy is the Extra Trees algorithm with affordable detection time. At the same time, the method has good learning efficiency indicators. This means that this algorithm can be deployed and applied with the greatest success. © 2024 IEEE.

关键词： network intrusion

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Intelligent Transmission Scheduling for Edge Sensing in Industrial IoT systems

Intelligent Transmission Scheduling for Edge Sensing in Indu...

引用

IEEE conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： Jin, Tiankai Ma, Yehan Ji, Zhiduo Chen, Cailian Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

ISBN: (纸本)9798350310900

Edge sensing supported by wireless transmission is one of the core enabling technologies for flexibly implementing the Industrial internet of Things (IIoT). Balancing network resource consumption and sensing accuracy under dynamic network conditions is a critical challenge. In this work, we bridge the gap between edge sensing performance and transmission design through observability analysis and learning-based methods. Particularly, utilizing observability probability as the key metric, we design the network resource reservation for specific sensing performance demands including stability based on our derived upper and lower probability bounds. Then, to further reduce the overall cost of edge sensing and transmission, an intelligent transmission scheduling method (ITSM) based on deep reinforcement learning is provided, which dynamically schedules the number of transmissions for each sensor. In ITSM, the action space is determined according to the amount of our reserved resources, and both the states of sensing error and fading channel are taken into account. Finally, the superiority of our proposed methods is fully demonstrated through numerical simulations in a typical IIoT system of industrial hot rolling.

关键词： Industrial internet of Things (IIoT) edge sensing observability transmission scheduling deep reinforcement learning

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Future-Proofed Intrusion Detection for internet of Things with Machine Learning 4

Future-Proofed Intrusion Detection for Internet of Things wi...

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4th IEEE International conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Adeyemi, Taiwo Ngobigha, Felix Ez-Zizi, Adnane University of Suffolk School of Technology Business and Arts Ipswich United Kingdom

ISBN: (纸本)9798331518882

The rapid increase in the deployment of internet-of-Things (IoT) devices necessitates robust intrusion detection systems. This study evaluates the effectiveness of machine learning models, including Decision Tree, Random Forest and XGBoost in classifying both known and emerging IoT malware threats. Using the CICIoT2023 dataset, we conducted analyses across binary, 8 -class and 34 -class classifications. Our findings demonstrate that Random Forest consistently outperforms other models, achieving near-perfect accuracy in binary classification and excellent results in multi-class scenarios. Notably, we observed almost no gains in performance beyond a dataset size of 1.5 million records, challenging the notion that larger datasets always equate to better models in malware detection. Furthermore, we investigated machine learning models' ability to detect zero-day attacks, showing that machine learning techniques offer robust and adaptive solutions for IoT intrusion detection, even in the face of emerging malware attacks. © 2025 IEEE.

关键词： network intrusion

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