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Consensus control of second-order stochastic discrete-time multi-agent systems without velocity transmission

Control Theory and technology 2023年第4期21卷 591-601页

作者： Zi-Xuan Wang Xiaofeng Zong Ling-Jie Gai School of Automation China University of GeosciencesWuhan430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuhanHubeiChina Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhanHubeiChina

This article studies the almost-sure and the mean-square consensus control problems of second-order stochastic discrete-time multi-agent systems with multiplicative ***,a control law based on the absolute velocity and relative position information is ***,considering the existence of multiplicative noises and nonlinear terms with Lipschitz constants,the consensus control problem is solved through the use of a degenerated Lyapunov ***,for the linear second-order multi-agent systems,some explicit consensus conditions are ***,two sets of numerical simulations are performed.

关键词： Consensus control Multiplicative noises Second-order Discrete-time Multi-agent system

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A comprehensive overview of AI based methods for SoC estimation of Li-ion Batteries in EV

A comprehensive overview of AI based methods for SoC estimat...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Ines Baccouche Najoua Essoukri Ben Amara Ecole Nationale d’Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Sousse Tunisie

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

State of charge (SoC) estimation is a critical aspect of managing lithium-ion (Li-ion) batteries in electric vehicles (EVs). Various Artificial Intelligence (AI) techniques have been used to enhance SoC estimation accuracy, such as convolutional neural networks, recurrent neural networks, generative networks, and more. This article provides a thorough survey of AI-based models utilized for SoC estimation in Li-ion batteries, synthesizing findings from diverse studies. By comparing the performance of different models : classical Machine Learning, convolutional, recurrent and generative, insights into the effectiveness and limitations of various AI approaches are highlighted. The review aims to guide future research efforts toward developing robust and accurate SoC estimation methods crucial for optimizing EV battery management systems.

关键词： Lithium-ion batteries Training Surveys Accuracy Reviews Estimation Data models State of charge Reliability Artificial intelligence

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Adaptive Sliding-Mode Observer for FOC of IM Drives Fed by Soft-VSI Topology: Wind Turbine Emulator Application

Adaptive Sliding-Mode Observer for FOC of IM Drives Fed by S...

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International Conference on advanced systems and Electric Technologies (IC_ASET)

作者： Mouna Zerzeri Intissar Moussa Adel Khedher LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Ecole Nationale d'Ingénieurs de Sousse Sousse Tunisie LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Institut Supérieur de Transport de la Logistique de Sousse Sousse Tunisie

ISBN: (数字)9798350384895

ISBN: (纸本)9798350384901

A novel adaptive sliding-mode observer scheme is introduced to enhance the field-oriented control of a Wind Tur-bine Emulator (WTE) designed around a three-phase induction motor fed by a soft-voltage source inverter (VSI) topology. A Mexican hat profile is applied as input for WTE system. The proposed adaptive observer efficiently detects rotor flux components and facilitates online estimation of motor resistive parameters, ensuring continuous tracking of rotor resistance. The analytical development of the sliding mode observer and the adaptive scheme, based on Lyapunov theory, is comprehensively explained. To validate the efficacy of the proposed adaptive observer structure, simulation results from a purpose-designed Matlab/Simulink model are presented.

关键词： Adaptation models Adaptive systems Uncertainty Simulation Rotors Observers Robustness

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Evaluation of Adjacent and Opposite Current Injection Patterns for 3D Image Reconstruction of the Human Lung Based on a Realistic Model 17

Evaluation of Adjacent and Opposite Current Injection Patter...

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17th International Workshop on Impedance Spectroscopy, IWIS 2024

作者： Bouchhima, Mejda Bader, Oumaima Hafsa, Mariem Sahnoun, Salwa Ben Amara, Najoua Essoukri Kanoun, Olfa National School of Electronics and Telecommunications of Sfax University of Sfax Sfax3038 Tunisia Professorship Measurement and Sensor Technology Chemnitz University of Technology Chemnitz09111 Germany Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS - Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Center of Sfax Sfax3038 Tunisia

ISBN: (纸本)9798331507626

Electrical Impedance Tomography (EIT) is a non-invasive, radiation-free imaging technique that can be used for 2D lung imaging. However, 2D EIT has a simplified geometric assumption, which neglects the 3D dynamic lung changes. This study develops a realistic 3D geometrical model including the lungs and thoracic cavity For EIT analysis. Finite Element (FE) models are generated for forward calculation and image reconstruction using an optimized Gauss-Newton (GN) algorithm. Two common current injection patterns - Adjacent and Opposite - are compared. Results show that using the lung-refined model with prior knowledge of the lungs' elements, GN converges with a Pearson correlation (r) of 0.9707 for the opposite pattern, higher than the adjacent pattern which reaches 0.9703. The second metric is the mean squared errors (MSE) between boundary voltages (BV) from reconstructed images and ground truth. It reaches 5.3965 · 10-4,5.3963· 10-4, and 1.0276· 10-12 for the Opposite pattern, respectively, for an empty cavity, lung-refined mesh without, and with prior knowledge of the lungs' elements. The results prove the efficiency of the Opposite injection pattern compared to the Adjacent pattern. These findings highlight the importance of injection patterns and the benefits of using a lung-refined mesh with prior knowledge of the lungs' elements for more accurate reconstructions. © 2024 IEEE.

关键词： Mesh generation

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An Overview of In Vitro Biological Neural Networks for Robot Intelligence

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Cyborg and Bionic systems 2023年第1期4卷 523-539页

作者： Zhe Chen Qian Liang Zihou Wei Xie Chen Qing Shi Zhiqiang Yu Tao Sun School of Medical Technology Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 10081China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China

In vitro biological neural networks(BNNs)interconnected with robots,so-called BNN-based neurorobotic systems,can interact with the external world,so that they can present some preliminary intelligent behaviors,including learning,memory,robot control,*** work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems,with a particular focus on those related to robot *** this work,we first introduce the necessary biological background to understand the 2 characteristics of the BNNs:nonlinear computing capacity and network ***,we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects:from robots to BNNs and from BNNs to ***,we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity(computing capacity-dependent)or depend also on the network plasticity(network plasticity-dependent),which are then expounded respectively,with a focus on those related to the realization of robot ***,the development trends and challenges of the BNNbased neurorobotic systems are discussed.

关键词： robot Robot networks

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VisualIE: Receipt-Based Information Extraction with a Novel Visual and Textual Approach

VisualIE: Receipt-Based Information Extraction with a Novel ...

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International Conference on Cyberworlds

作者： Hamza Gbada Karim Kalti Mohamed Ali Mahjoub Higher Institute of Informatics and Communication Technologies University of Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems National Engineering School of Sousse (ENISo) Sousse Tunisia Faculty of sciences of Monastir University of Monastir LATIS-Laboratory of Advanced Technology and Intelligent Systems National Engineering School of Sousse (ENISo) Monastir Tunisia LATIS-Laboratory of Advanced Technology and Intelligent Systems National Engineering School of Sousse (ENISo) Sousse Tunisia

Information extraction (IE) from a receipt-based document requires understanding the contextual and visual semantics of texts. However, prior studies have predominantly utilized pre-trained language models and Optical Character Recognition (OCR) engines to extract textual features from the document and conduct entity extraction. Besides, this paper presents a novel approach for information extraction from receipt-based documents by leveraging both visual and textual features. The proposed approach employs a convolutional neural network to capture visual features and a word embedding model to capture textual features. These features are then combined and fed into a fully connected layer for entity classification. The experimental results demonstrate that the proposed approach outperforms the baseline and achieves state-of-the-art results in information extraction from receipts.

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Ultrasensitive SERF atomic magnetometer with a miniaturized hybrid vapor cell

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Microsystems & Nanoengineering 2024年第4期10卷 367-376页

作者： Yintao Ma Yao Chen Mingzhi Yu Yanbin Wang Shun Lu Ju Guo Guoxi Luo Libo Zhao Ping Yang Qijing Lin Zhuangde Jiang State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemsXi’an Jiaotong UniversityXi’an 710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China School of Instrument Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing YantaiYantai 265503China

The chip-scale hybrid optical pumping spin-exchange relaxation-free(SERF)atomic magnetometer with a single-beam arrangement has prominent applications in biomagnetic measurements because of its outstanding features,including ultrahigh sensitivity,an enhanced signal-to-noise ratio,homogeneous spin polarization and a much simpler optical configuration than other *** this work,a miniaturized single-beam hybrid optical pumping SERF atomic magnetometer based on a microfabricated atomic vapor cell is *** the optically thin Cs atoms are spinpolarized,the dense Rb atoms determine the experimental *** enhanced signal strength and narrowed resonance linewidth are experimentally proven,which shows the superiority of the proposed magnetometer *** using a differential detection scheme,we effectively suppress optical noise with an approximate five-fold ***,the cell temperature markedly affects the performance of the *** systematically investigate the effects of temperature on the magnetometer *** theoretical basis for these effects is explained in *** developed miniaturized magnetometer has an optimal magnetic sensitivity of 20 fT/Hz^(1/2).The presented work provides a foundation for the chip-scale integration of ultrahighly sensitive quantum magnetometers that can be used for forward-looking magnetocardiography(MCG)and magnetoencephalography(MEG)applications.

关键词： pumping polarization magnetometer

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Design and fabrication of a gecko-inspired surface for improving the grasping ability of a humanoid dexterous hand

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Science China(Technological Sciences) 2023年第3期66卷 784-792页

作者： JIANG ZhiHong SHEN MingHui MA YiFan CHE JiangTao LI Hui School of Mechatronic Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing 100081China Key Laboratory of Biomimetic Robots and Systems Ministry of EducationBeijing 100081China China Electronics Standardization Institute Beijing 100007China

Many studies have examined the design,fabrication and characteristics of gecko-inspired adhesives,but applied research on gecko-inspired surfaces in humanoid dexterous hands is relatively ***,a wedged slanted structure with a curved substrate suitable for humanoid dexterous fingers was designed and manufactured via ultraprecision machining and replica *** adhesion and friction properties of the wedged slanted structure show obvious anisotropic characteristics in the gripping and releasing directions,and the influence of structural parameters and motion parameters on the adhesion and friction was systematically *** humanoid dexterous fingers with gecko-inspired surfaces greatly increased the grasping force limit(increase to 4.02 times)based on the grasping of measuring cups with different volumes of water and improved the grasping stability based on the picking up of smooth steel balls of different *** study shows that this process,based on ultraprecision machining and replica molding,is a green,high-efficiency,and low-cost method to fabricate large-area biomimetic surfaces that has potential applications in dexterous humanoid hands to improve grasping ability,stability and adaptability.

关键词： gecko-inspired surface curved substrate ultraprecision machining friction humanoid dexterous hand

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Enhanced Detection of Copy-Move Forgery by Fusing Scores From Handcrafted and Deep Learning-Based Detection systems

Enhanced Detection of Copy-Move Forgery by Fusing Scores Fro...

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International Conference on Developments in esystems Engineering (DESE)

作者： Issam Shallal Lamia Rzouga Haddada Najoua Essoukri Ben Amara Université de Sousse Institut Supérieur d’Informatique et des Techniques de Communication de H. Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisia Université de Sousse Institut Supérieur des Sciences Appliquées et de Technologie de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisia Université de Sousse Ecole Nationale d’Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisia

ISBN: (数字)9798350368697

ISBN: (纸本)9798350368703

With the advancement and widespread use of digital devices, capturing images has become effortless in any location. Images serve as evidence, making the authenticity of digital images increasingly critical. Some individuals alter images by adding or removing elements, rendering the images unreliable. Consequently, detecting image forgery has become essential. The evolution of image editing software has intensified this issue within the realm of computer vision. Recently, a variety of algorithms have been developed to identify image forgery. However, with the progress in digital technology, the ease of image manipulation has led to a surge in forgery cases, presenting significant obstacles when verifying their authenticity. Thus, there is a pressing requirement for effective forgery detection methods. This paper introduces a novel copy-move forgery detection approach based on the fusion of a handcrafted forgery detection system utiliszing the scale-invariant feature transform and the support vector machine with a deep-learning-based forgery detection system using VGG16. The aim is to address the challenges of subtle forgery detection and blending and seamless Integration. We conduct the experiments on the MICC_F2000 image manipulation dataset and assess the efficacy of the proposed approach, achieving $\mathbf{9 6 . 7 5 \%}$ accuracy, $\mathbf{1 0 0 \%}$ precision and $95.5 \%$ F1-score. This research demonstrates superior performance compared to state-of-the-art methods.

关键词： Support vector machines Deep learning Accuracy Digital images Forensics Software algorithms Transforms Feature extraction Forgery Surges

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Safe Efficient Policy Optimization Algorithm for Unsignalized Intersection Navigation

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 2011-2026页

作者： Xiaolong Chen Biao Xu Manjiang Hu Yougang Bian Yang Li Xin Xu State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body the College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body the College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082 Wuxi Intelligent Control Research Institute(WICRI)of Hunan University Wuxi 214115China College of Intelligence Science and Technology Institute of Unmanned SystemsNational University of Defense TechnologyChangsha 410073China

Unsignalized intersections pose a challenge for autonomous vehicles that must decide how to navigate them safely and *** paper proposes a reinforcement learning(RL)method for autonomous vehicles to navigate unsignalized intersections safely and *** method uses a semantic scene representation to handle variable numbers of vehicles and a universal reward function to facilitate stable learning.A collision risk function is designed to penalize unsafe actions and guide the agent to avoid them.A scalable policy optimization algorithm is introduced to improve data efficiency and safety for vehicle learning at *** algorithm employs experience replay to overcome the on-policy limitation of proximal policy optimization and incorporates the collision risk constraint into the policy optimization *** proposed safe RL algorithm can balance the trade-off between vehicle traffic safety and policy learning *** intersection scenarios with different traffic situations are used to test the algorithm and demonstrate its high success rates and low collision rates under different traffic *** algorithm shows the potential of RL for enhancing the safety and reliability of autonomous driving systems at unsignalized intersections.

关键词： Autonomous driving decision-making reinforcement learning(RL) unsignalized intersection

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