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Distributed Nash Equilibrium Seeking Strategies Under Quantized Communication

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 103-112页

作者： Maojiao Ye Qing-Long Han lei ding Shengyuan Xu Guobiao Jia IEEE the School of Automation Nanjing University of Science and TechnologyNanjing 210094China the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the Institute of Advanced Technology Nanjing University of Posts and TelecommunicationsNanjing 210023China

This paper is concerned with distributed Nash equi librium seeking strategies under quantized communication. In the proposed seeking strategy, a projection operator is synthesized with a gradient search method to achieve the optimization o players' objective functions while restricting their actions within required non-empty, convex and compact domains. In addition, a leader-following consensus protocol, in which quantized informa tion flows are utilized, is employed for information sharing among players. More specifically, logarithmic quantizers and uniform quantizers are investigated under both undirected and connected communication graphs and strongly connected digraphs, respec tively. Through Lyapunov stability analysis, it is shown that play ers' actions can be steered to a neighborhood of the Nash equilib rium with logarithmic and uniform quantizers, and the quanti fied convergence error depends on the parameter of the quan tizer for both undirected and directed cases. A numerical exam ple is given to verify the theoretical results.

关键词： Consensus distributed Nash equilibrium seeking projected gradient play quantized communication

MXenes/CNTs-based hybrids:Fabrications,mechanisms,and modification strategies for energy and environmental applications

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Nano Research 2024年第5期17卷 3429-3454页

作者： Jizhou Jiang Fangyi Li lei ding Chengxun Zhang Arramel Xin Li School of Environmental Ecology and Biological Engineering School of Chemistry and Environmental EngineeringKey Laboratory of Green Chemical Engineering Process of Ministry of EducationEngineering Research Center of Phosphorus Resources Development and Utilization of Ministry of EducationNovel Catalytic Materials of Hubei Engineering Research CenterWuhan Institute of TechnologyWuhan 430205China Nano Center Indonesia Jl.PUSPIPTEK Tangerang SelatanBanten 15314Indonesia Institute of Biomass Engineering Key Laboratory of Energy Plants Resource and UtilizationMinistry of Agriculture and Rural AffairsSouth China Agricultural UniversityGuangzhou 510642China

Emerging two-dimensional(2D)layered metal carbide and nitride materials,commonly termed MXenes,are increasingly recognized for their applications across diverse fields such as energy,environment,and catalysis.In the past few years,MXenes/carbon nanotubes(CNTs)-based hybrids have attracted extensive attention as an important catalyst in energy and environmental fields,due to their superior multifunctions and mechanical stability.This review aims to address the fabrication strategies,the identification of the enhancement mechanisms,and recent progress regarding the design and modification of MXenes/CNTs-based hybrids.A myriad of fabrication techniques have been systematically summarized,including mechanical mixing,spray drying,three-dimensional(3D)printing,self-assembly/in-situ growth,freeze drying,templating,hydrothermal methods,chemical vapor deposition(CVD),and rolling.Importantly,the identification of the enhancement mechanisms was thoroughly discussed from the two dimensions of theoretical simulations and in-situ analysis.Moreover,the recent advancements in profound applications of MXenes/CNTs-based hybrids have also been carefully revealed,including energy storage devices,sensors,water purification systems,and microwave absorption.We also underscore anticipated challenges related to their fabrication,structure,underlying mechanisms,modification approaches,and emergent applications.Consequently,this review offers insights into prospective directions and the future trajectory for these promising hybrids.It is expected that this review can inspire new ideas or provide new research methods for future studies.

关键词： MXenes/carbon nanotubes(CNTs)-based hybrids fabrication applications modification strategies

Dynamic motion of quadrupedal robots on challenging terrain:a kinodynamic optimization approach

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Frontiers of Mechanical Engineering 2024年第3期19卷 23-40页

作者： Qi LI lei ding Xin LUO Engineering Research Center of Hubei Province for Clothing Information Wuhan 430200China School of Computer Science and Artificial Intelligence Wuhan Textile UniversityWuhan 430200China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China

The dynamic motion of quadrupedal robots on challenging terrain generally requires elaborate spatial–temporal kinodynamic motion planning and accurate control at higher refresh rate in comparison with regular terrain.However,conventional quadrupedal robots usually generate relatively coarse planning and employ motion replanning or reactive strategies to handle terrain irregularities.The resultant complex and computation-intensive controller may lead to nonoptimal motions or the breaking of locomotion rhythm.In this paper,a kinodynamic optimization approach is presented.To generate long-horizon optimal predictions of the kinematic and dynamic behavior of the quadruped robot on challenging terrain,we formulate motion planning as an optimization problem;jointly treat the foot’s locations,contact forces,and torso motions as decision variables;combine smooth motion and minimal energy consumption as the objective function;and explicitly represent feasible foothold region and friction constraints based on terrain information.To track the generated motions accurately and stably,we employ a whole-body controller to compute reference position and velocity commands,which are fed forward to joint controllers of the robot’s legs.We verify the effectiveness of the developed approach through simulation and on a physical quadruped robot testbed.Results show that the quadruped robot can successfully traverse a 30°slope and 43% of nominal leg length high step while maintaining the rhythm of dynamic trot gait.

关键词： quadrupedal robot kinodynamic planning nonlinear optimization challenging terrain whole-body control

IoV environment exploring coordination:A federated learning approach

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Digital Communications and Networks 2024年第1期10卷 135-141页

作者： Tong ding lei Liu Yi Zhu Lizhen Cui Zhongmin Yan School of Software Shandong UniversityJinan250101China

Exploring open fields with coordinated unmanned vehicles is popular in academia and industries.One of the most impressive applicable approaches is the Internet of Vehicles(lov).The IoV connects vehicles,road infrastructures and communication facilities to provide solutions for exploration tasks.However,the coordination of acquiring information from multi-vehicles may risk data privacy.To this end,sharing high-quality experiences instead of raw data has become an urgent demand.This paper employs a Deep Reinforcement Learning(DRL)method to enable IoVs to generate training data with prioritized experience and states,which can support the IoV to explore the environment more efficiently.Moreover,a Federated Learning(FL)experience sharing model is established to guarantee the vehicles'privacy.The numerical results show that the proposed method presents a better successful sharing rate and a more stable convergence within the comparison of fundamental methods.The experiments also suggest that the proposed method could support agents without full information to achieve the tasks.

关键词： Internet of vehicle Deep reinforcement learning Federated learning Data privacy

Chord length sampling correction analysis for dispersion fuel in Monte Carlo simulation

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Nuclear Science and Techniques 2024年第4期35卷 57-64页

作者： Zhao-Yu Liang ding She Yu-Tong Wen lei Shi Institute of Nuclear and New Energy Technology(INET) Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of EducationTsinghua UniversityBeijing 100084China

Dispersion fuels,knowned for their excellent safety performance,are widely used in advanced reactors,such as hightemperature gas-cooled reactors.Compared with deterministic methods,the Monte Carlo method has more advantages in the geometric modeling of stochastic media.The explicit modeling method has high computational accuracy and high computational cost.The chord length sampling(CLS)method can improve computational efficiency by sampling the chord length during neutron transport using the matrix chord length?s probability density function.This study shows that the excluded-volume effect in realistic stochastic media can introduce certain deviations into the CLS.A chord length correction approach is proposed to obtain the chord length correction factor by developing the Particle code based on equivalent transmission probability.Through numerical analysis against reference solutions from explicit modeling in the RMC code,it was demonstrated that CLS with the proposed correction method provides good accuracy for addressing the excludedvolume effect in realistic infinite stochastic media.

关键词： Stochastic media Monte Carlo Chord length sampling Excluded-volume effect Chord length correction

Synthesis of hierarchically porous carbon materials by zinc salts-assisted carbonization of biomass and organic solid wastes

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Particuology 2024年第1期84卷 45-52页

作者： Le-Le Zhang lei Tong Yanwei ding Wanqun Zhang Hai-Wei Liang Hefei National Research Center for Physical Sciences at the Microscale Department of ChemistryUniversity of Science and Technology of ChinaHefei230026China

Hierarchically porous carbons(HPCs)with multimodal pores have attracted considerable attention due to their unique physical and chemical properties and various application potentials in heterogeneous catalysis,environmental treatment,and energy storage and conversion.Herein,we report a general and simple zinc salts-assisted method for the synthesis of HPCs with varied porosity and chemical func-tionalities by the direct carbonization of diverse biomass and wastes.During the carbonization,zinc salts are thermally decomposed into nanoparticles that serve as in-situ templates to introduce nanopores in carbons.The prepared HPCs exhibit high specific surface areas(up to 2432 m2 g-1),large pore volumes(up to 4.30 cm^(3)g^(-1)),and broad pore size distributions.Moreover,the zinc salts can be recovered and recycled,supporting the sustainable production of HPCs on large scale.The prepared HPCs-supported catalysts with atomically dispersed metal sites exhibit promising electrocatalytic performance for the oxygen reduction reaction.

关键词： Hierarchical porous carbon Zinc salts Biomass Wastes Electrocatalysis

Tumor necrosis factor-stimulated gene-6 ameliorates early brain injury after subarachnoid hemorrhage by suppressing NLRC4 inflammasome-mediated astrocyte pyroptosis

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Neural Regeneration Research 2024年第5期19卷 1064-1071页

作者： Mingxiang ding lei Jin Boyang Wei Wenping Cheng Wenchao Liu Xifeng Li Chuanzhi Duan Neurosurgery Center Department of Cerebrovascular SurgeryThe National Key Clinical SpecialtyThe Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular DiseaseGuangdong Provincial Key Laboratory on Brain Function Repair and RegenerationThe Neurosurgery Institute of Guangdong ProvinceZhujiang HospitalSouthern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Cerebrovascular Intervention Zhongshan City People’s HospitalZhongshanGuangdong ProvinceChina

Subarachnoid hemorrhage is associated with high morbidity and mortality and lacks effective treatment.Pyroptosis is a crucial mechanism underlying early brain injury after subarachnoid hemorrhage.Previous studies have confirmed that tumor necrosis factor-stimulated gene-6(TSG-6)can exert a neuroprotective effect by suppressing oxidative stress and apoptosis.However,no study to date has explored whether TSG-6 can alleviate pyroptosis in early brain injury after subarachnoid hemorrhage.In this study,a C57BL/6J mouse model of subarachnoid hemorrhage was established using the endovascular perforation method.Our results indicated that TSG-6 expression was predominantly detected in astrocytes,along with NLRC4 and gasdermin-D(GSDMD).The expression of NLRC4,GSDMD and its N-terminal domain(GSDMD-N),and cleaved caspase-1 was significantly enhanced after subarachnoid hemorrhage and accompanied by brain edema and neurological impairment.To explore how TSG-6 affects pyroptosis during early brain injury after subarachnoid hemorrhage,recombinant human TSG-6 or a siRNA targeting TSG-6 was injected into the cerebral ventricles.Exogenous TSG-6 administration downregulated the expression of NLRC4 and pyroptosis-associated proteins and alleviated brain edema and neurological deficits.Moreover,TSG-6 knockdown further increased the expression of NLRC4,which was accompanied by more severe astrocyte pyroptosis.In summary,our study revealed that TSG-6 provides neuroprotection against early brain injury after subarachnoid hemorrhage by suppressing NLRC4 inflammasome activation-induced astrocyte pyroptosis.

关键词： astrocyte early brain injury inflammasome NLRC4 pyroptosis subarachnoid hemorrhage tumor necrosis factor-stimulated gene-6(TSG-6)

Integrated Active Suspension and Anti-Lock Braking Control for Four-Wheel-Independent-Drive Electric Vehicles

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 87-98页

作者： Ze Zhao lei Zhang Xiaoling ding Zhiqiang Zhang Shaohua Li Liang Gu National Engineering Research Center for Electric Vehicles Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China

This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system(ASS)and anti-lock braking system(ABS).First,a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input model.Then the coupling mechanisms between longitudinal and vertical vehicle dynamics are analyzed.An ASS-ABS integrated control system is proposed,utilizing an H∞controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS implementation.Finally,the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop(HIL)test platform.The HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods.

关键词： Four-wheel-independent-drive electric vehicles Active suspension system(ASS) Anti-lock braking system(ABS) Vertical-longitudinal vehicle dynamics

Strengthening Network Security: Deep Learning Models for Intrusion Detectionwith Optimized Feature Subset and Effective Imbalance Handling

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Computers, Materials & Continua 2024年第2期78卷 1995-2022页

作者： Bayi Xu lei Sun Xiuqing Mao Chengwei Liu Zhiyi ding School of Cyber Science and Engineering Zhengzhou UniversityZhengzhou450000China Three Academy Information Engineering UniversityZhengzhou450001China The 3rd Research Department Nanjing Research Institute of Electronic EngineeringNanjing210007China

In recent years,frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security.This paper presents a novel intrusion detection system consisting of a data prepro-cessing stage and a deep learning model for accurately identifying network attacks.We have proposed four deep neural network models,which are constructed using architectures such as Convolutional Neural Networks(CNN),Bi-directional Long Short-Term Memory(BiLSTM),Bidirectional Gate Recurrent Unit(BiGRU),and Attention mechanism.These models have been evaluated for their detection performance on the NSL-KDD dataset.To enhance the compatibility between the data and the models,we apply various preprocessing techniques and employ the particle swarm optimization algorithm to perform feature selection on the NSL-KDD dataset,resulting in an optimized feature subset.Moreover,we address class imbalance in the dataset using focal loss.Finally,we employ the BO-TPE algorithm to optimize the hyperparameters of the four models,maximizing their detection performance.The test results demonstrate that the proposed model is capable of extracting the spatiotemporal features of network traffic data effectively.In binary and multiclass experiments,it achieved accuracy rates of 0.999158 and 0.999091,respectively,surpassing other state-of-the-art methods.

关键词： Intrusion detection CNN BiLSTM BiGRU attention