IEEE Transactions on Systems Man Cybernetics-Systems最新文献_第2页

An Adaptive Fuzzy Rough Neural Network and Its Application in Classification 自适应模糊粗糙神经网络及其在分类中的应用

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-26 DOI: 10.1109/TSMC.2025.3599882

Changzhong Wang;Yang Zhang;Shuang An;Weiping Ding

{"title":"An Adaptive Fuzzy Rough Neural Network and Its Application in Classification","authors":"Changzhong Wang;Yang Zhang;Shuang An;Weiping Ding","doi":"10.1109/TSMC.2025.3599882","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3599882","url":null,"abstract":"Fuzzy rough set theory is an important approach for analyzing data uncertainty. However, the model lacks adaptive learning capabilities and cannot fit labeled data effectively in classification tasks. This study aims to introduce an adaptive learning mechanism into fuzzy rough set theory to enhance its data-fitting capability. To this end, this study seamlessly integrates fuzzy rough set theory with neural networks and proposes a novel fuzzy rough neural network model. This model adaptively learns fuzzy similarity relations in rough set models using the backpropagation algorithm. The proposed network model comprises five layers: the input, membership, fuzzy lower approximation, fully connected, and output layers. The fuzzy similarity relations between the input samples and training samples are computed in the membership layer. These relations are utilized in the fuzzy lower approximation layer to describe the degree to which the samples belong to different classes. The fuzzy rough lower approximations of the input samples are finally fused in the fully connected layer using feature weight coefficients. In the backpropagation stage, the gradient of the objective function is used to correct the fuzzy similarity relations and feature weight coefficients. This study theoretically proved that the proposed fuzzy rough network has a generalized function approximation property and can approximate any decision function. Experimental analysis showed that the proposed method is effective and performs better than most of the existing state-of-the-art algorithms.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7579-7590"},"PeriodicalIF":8.7,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fixed-Time Sliding Mode Adaptive Control of Hydraulic Manipulator With Shutoff Deadzone and Uncertain Nonlinearity 具有关闭死区和不确定非线性的液压机械臂的定时滑模自适应控制

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-26 DOI: 10.1109/TSMC.2025.3598080

Qing Guo;Haoran Zhan;Zhao Wang;Tieshan Li

{"title":"Fixed-Time Sliding Mode Adaptive Control of Hydraulic Manipulator With Shutoff Deadzone and Uncertain Nonlinearity","authors":"Qing Guo;Haoran Zhan;Zhao Wang;Tieshan Li","doi":"10.1109/TSMC.2025.3598080","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3598080","url":null,"abstract":"There exist general model uncertainty and shutoff deadzone in hydraulic-driving plant due to unknown model parameters of mechanical structure and physical feature of electrohydraulic actuator, which will degrade the motion performance and stability. In this study, a fixed-time sliding mode adaptive control is presented in 2-DOF hydraulic manipulator to address these issues. First, the dynamic manipulator with two degree-of-freedom joint driving by hydraulic servo valve is setup via Lagrangian method. Then, a sliding mode disturbance observer is designed to approximate uncertain nonlinearity to ensure the lumped uncertainties convergence in a practical finite time. Furthermore, a parametric adaptive estimation is used to estimate unknown shutoff deadzone parameters. According to backstepping technique, a fixed-time convergence control is adopted to ensure all the system state errors converge into a zero neighborhood in a constant time not related to any initial condition. Finally, the fixed-time sliding mode adaptive controller has been verified in an experimental bench of 2-DOF manipulator.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7566-7578"},"PeriodicalIF":8.7,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vertical Information Sharing in a Blockchain-Enabled Supply Chain 基于区块链的供应链中的垂直信息共享

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-22 DOI: 10.1109/TSMC.2025.3595714

Mingyang Chen;Yeming Gong

{"title":"Vertical Information Sharing in a Blockchain-Enabled Supply Chain","authors":"Mingyang Chen;Yeming Gong","doi":"10.1109/TSMC.2025.3595714","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3595714","url":null,"abstract":"While previous studies have examined how blockchain adoption affects stakeholders’ decision-making, the vertical demand information-sharing among supply chain members within a blockchain framework remains underexplored, which raises the question of how a blockchain-enabled retailer shares the demand information and how the blockchain technology may work in a supply chain. This study investigates the impacts of introducing blockchain technology on the information-sharing strategy and equilibrium choice. We find that, in the scenario of blockchain technology, information sharing may not occur when the product quality is higher since sharing may benefit the upstream and hurt the downstream. When the quality is lower, information sharing can be better off for all members given the conditions: 1) the market dispersion is larger or 2) the market dispersion is smaller and the cost is higher. In the scenario of no information-sharing, the implementation of blockchain technology is always better off for the supplier due to the increase in the wholesale price and order quantity, while conditionally benefiting the retailer if the implementation cost of blockchain technology is lower. We also find that consumer surplus is lowest in the case of no information-sharing and no blockchain because of the higher price and nontraceability of information.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7459-7471"},"PeriodicalIF":8.7,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Historical Data-Based Reinforcement Learning for Pursuit–Evasion Games of Nonholonomic Vehicles With Input Saturation 输入饱和非完整车辆追逃博弈的动态历史数据强化学习

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-22 DOI: 10.1109/TSMC.2025.3595891

Fei Zhang;Guang-Hong Yang

{"title":"Dynamic Historical Data-Based Reinforcement Learning for Pursuit–Evasion Games of Nonholonomic Vehicles With Input Saturation","authors":"Fei Zhang;Guang-Hong Yang","doi":"10.1109/TSMC.2025.3595891","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3595891","url":null,"abstract":"This article studies the pursuit–evasion game involving nonholonomic vehicles constrained by input saturation, aiming for the pursuer to intercept an evasive opponent. Unlike the previous game research neglecting the practical kinematic constraints, a coupled nonlinear system is formulated to elucidate the interaction dynamics between the players. After that, the optimal control strategies are derived by solving the Hamilton–Jacobi–Isaacs (HJI) equation linked to a special nonquadratic cost function. The Nash equilibrium analysis and finite-time capturability are conducted. To learn the optimal pursuit–evasion strategy pair, a fixed-time convergent reinforcement learning (RL) algorithm is proposed, which leverages a novel residual design to facilitate weight updates by collecting and evaluating current and historical data based on information quality. Compared with the existing RL methods that suffer from sluggish convergence due to an asymptotic learning rule and the stringent persistent excitation (PE) condition, the proposed RL relaxes the PE to an easily achievable and online verifiable finite excitation (FE) condition, allowing rapid weight convergence within a fixed period. Simulations and comparisons validate the effectiveness and superiority of the proposed method, showing a 61% reduction in convergence time in contrast to the prevailing RL schemes.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7539-7550"},"PeriodicalIF":8.7,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiplex Experts Governance Collaboration for Label Noise-Resistant Graph Representation Learning 标签抗噪声图表示学习的多专家治理协作

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-21 DOI: 10.1109/TSMC.2025.3595183

Sichao Fu;Qinmu Peng;Yiu-Ming Cheung;Yizhuo Xu;Bin Zou;Xiao-Yuan Jing;Xinge You

{"title":"Multiplex Experts Governance Collaboration for Label Noise-Resistant Graph Representation Learning","authors":"Sichao Fu;Qinmu Peng;Yiu-Ming Cheung;Yizhuo Xu;Bin Zou;Xiao-Yuan Jing;Xinge You","doi":"10.1109/TSMC.2025.3595183","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3595183","url":null,"abstract":"Recently emerged label noise-resistant graph representation learning (LNR-GRL) has received increasing attention, which aims to enhance the generalization of graph neural networks (GNNs) in semi-supervised node classification with noisy and limited labels. Most of the existing LNR-GRL tend to introduce more complex sample selection strategies developed in nongraph areas to distinguish more noisy nodes to alleviate their misguidance. However, these proposed methods neglect the importance of inaccurate graph structure relationships rectification, and information collaboration between inaccurate graph structure relationships and noisy node label rectification in improving the quality of noisy node identification and its rectified node labels. To solve the above-mentioned issues, we propose a novel multiplex experts governance collaboration (MEGC) framework for LNR-GRL. Specifically, an unsupervised graph structure governance expert is first designed to rectify inaccurate graph structure relationships. Based on the rectified graph structure, a simple label noise governance expert is proposed to accurately identify noisy node labels and further improve the quality of noisy nodes’ rectified labels and unlabeled nodes’ pseudo-labels. Finally, the above-proposed governance experts can be effectively combined with GNNs to jointly guide their training via the introduced cross-view graph contrastive loss and cross-entropy loss, which can maximally limit the effect of noisy node labels and discover more effective supervision guidance from data itself for GNNs optimization. Extensive experiments on three benchmarks, two label noise types, four noise rates, and four training label rates demonstrate the superiority of the proposed method in comparison to the existing LNR-GRL methods.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7437-7448"},"PeriodicalIF":8.7,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Transmission Scheduling for Remote State Estimation Under Active Eavesdropping-Based DoS Attacks 基于主动窃听的DoS攻击下远程状态估计的最优传输调度

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-21 DOI: 10.1109/TSMC.2025.3595565

Yuan-Cheng Sun;Kui Gao;Liwei Chen;Feisheng Yang;Liwei An

{"title":"Optimal Transmission Scheduling for Remote State Estimation Under Active Eavesdropping-Based DoS Attacks","authors":"Yuan-Cheng Sun;Kui Gao;Liwei Chen;Feisheng Yang;Liwei An","doi":"10.1109/TSMC.2025.3595565","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3595565","url":null,"abstract":"In this article, the optimal transmission scheduling problem for remote state estimation over signal-to-interference-plus-noise ratio-based network channel is studied, in the presence of an active attacker who is able to implement DoS attacks to jam the network based on the eavesdropping information. An intelligent sensor is used to send the local state estimates to a remote estimator, and by co-designing the power control and the scheduling decision such that the sensor can decide whether to transmit and what power to use for communication, a coupling transmission strategy is provided. To minimize the energy consumption and the known estimation error covariance (EEC) of the remote estimator for the sensor, while maximizing the unknown eavesdropping EEC, the co-design scheduling issue is modeled as a modified Markov decision process by applying a Monte Carlo method based on a belief state probability distribution. A Clipped HetUpSoft Q-learning algorithm is designed to achieve the approximate optimal strategy online. Finally, simulation results are provided to validate the effectiveness of the developed approaches.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7487-7498"},"PeriodicalIF":8.7,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Observer-Based Fault-Tolerant Control for Switched Stochastic Nonlinear Systems With Nonlinear Exogenous Disturbance 具有非线性外源扰动的切换随机非线性系统的动态观测器容错控制

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-20 DOI: 10.1109/TSMC.2025.3595169

Jian Han;Jiuling Zhang;Xiuhua Liu;Xinjiang Wei

引用次数: 0

Extended Stability Envelopes and Effectiveness Quantification for Integrated Chassis Control With Multiple Actuator Configurations in the Energy Phase Plane 能量相位平面多作动器组合底盘控制的扩展稳定包络和有效性量化

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-20 DOI: 10.1109/TSMC.2025.3594736

Nan Xu;Zhuo Yin;Yuetao Zhang;Konghui Guo

{"title":"Extended Stability Envelopes and Effectiveness Quantification for Integrated Chassis Control With Multiple Actuator Configurations in the Energy Phase Plane","authors":"Nan Xu;Zhuo Yin;Yuetao Zhang;Konghui Guo","doi":"10.1109/TSMC.2025.3594736","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3594736","url":null,"abstract":"The emerged integrated chassis is playing an increasingly pivotal role in enhancing vehicle stability, which typically needs estimation of the stability envelope and proper coordination strategy for chassis controller design. The conventional stability envelope determined in phase plane ensure vehicle self-stability, while it neglects the influence of chassis actuators. To play out full performance of integrated chassis, this study proposes a novel extended stability envelope analysis method to quantify the effect of different chassis actuator combinations on vehicle lateral dynamic. In energy phase plane, the state change direction with influence of control inputs are employed to judge whether a given state will go beyond the tire’s grip limit. Accordingly extended stability envelopes of some typical actuator combinations, i.e., active front steering (AFS) and active rear steering (ARS), AFS and torque vectoring control (TVC), ARS and TVC, are determined. Meanwhile, principle to quantify the overlapping effectiveness range and unique effectiveness range between ARS and TVC is introduced, accordingly effectiveness factors used for coordination control are discussed. In summary, the proposed method in this article has considerable potential for coordination control of integrated chassis, by providing comprehensive analysis method to estimate the extended stability boundary and quantify the effectiveness range with influence of actuators taken into account.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7472-7486"},"PeriodicalIF":8.7,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection 基于全局正则化邻域回归的纹理零弹异常检测

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-20 DOI: 10.1109/TSMC.2025.3595539

Haiming Yao;Wei Luo;Yunkang Cao;Yiheng Zhang;Wenyong Yu;Weiming Shen

{"title":"Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection","authors":"Haiming Yao;Wei Luo;Yunkang Cao;Yiheng Zhang;Wenyong Yu;Weiming Shen","doi":"10.1109/TSMC.2025.3595539","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3595539","url":null,"abstract":"Texture surface anomaly detection finds widespread applications in industrial settings. However, existing methods often necessitate gathering numerous samples for model training. Moreover, they predominantly operate within a closed-set detection framework, limiting their ability to identify anomalies beyond the training dataset. To tackle these challenges, this article introduces a novel zero-shot texture anomaly detection method named global-regularized neighborhood regression (GRNR). Unlike conventional approaches, GRNR can detect anomalies on arbitrary textured surfaces without any training data or cost. Drawing from human visual cognition, GRNR derives two intrinsic prior supports directly from the test texture image: local neighborhood priors characterized by coherent similarities and global normality priors featuring typical normal patterns. The fundamental principle of GRNR involves utilizing the two extracted intrinsic support priors for self-reconstructive regression of the query sample. This process employs the transformation facilitated by local neighbor support while being regularized by global normality support, aiming to not only achieve visually consistent reconstruction results but also preserve normality properties. We validate the effectiveness of GRNR across various industrial scenarios using eight benchmark datasets, demonstrating its superior detection performance without the need for training data. Remarkably, our method is applicable for open-set texture defect detection and can even surpass existing vanilla approaches that require extensive training.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7510-7525"},"PeriodicalIF":8.7,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Manifesting Nominal Assistance in Hemiplegia Gait Training Through an Assistive Normality Framework 通过辅助正常框架在偏瘫步态训练中体现名义援助

IF 8.7 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-20 DOI: 10.1109/TSMC.2025.3595211

Wanxin Chen;Bi Zhang;Zhihai Li;Lianqing Liu;Haibin Yu;Xingang Zhao

{"title":"Manifesting Nominal Assistance in Hemiplegia Gait Training Through an Assistive Normality Framework","authors":"Wanxin Chen;Bi Zhang;Zhihai Li;Lianqing Liu;Haibin Yu;Xingang Zhao","doi":"10.1109/TSMC.2025.3595211","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3595211","url":null,"abstract":"Rehabilitation exoskeletons have been demonstrated to benefit mobility-limited patients; however, accessibility is hindered by several challenges, and interaction evaluation of coupled human–exoskeleton systems remains critically understudied. In this pioneering study, “assistive normality (AN)” is introduced to characterize the cross-stage spatiotemporal features of exoskeleton-assisted gait in hemiplegic patients, and a multidimensional, low-data-cost metric framework is developed to quantify AN. Three subdivided metrics, including gait restoration (GR), phase-deviation weighting (PDW) and multijoint coordination (MJC), are proposed to assess coupled system interaction behavior across different intervention stages during rehabilitation. A homologous difference evaluation paradigm (HDEP) is introduced to capture pathological differences between healthy and hemiplegic subjects on the basis of the reusability of experimental data, providing an approach for the nominal assistance calibration and assessment of specific exoskeleton devices. In a pilot study with eight healthy individuals and nine hemiplegic patients, between-group metric differences were analyzed to determine the calibrated AN of an exoskeleton. The results provide calibration references for quantitative metrics and demonstrate the ability of framework to characterize the temporal dynamics of human–exoskeleton interactions. The proposed AN framework offers a generalizable approach to assistive robotics, potentially enhancing evaluation of human-robot interaction and advancing clinical rehabilitation applications.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7526-7538"},"PeriodicalIF":8.7,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0