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

Deep Active Learning for Image Hierarchical Classification by Introducing Dependencies and Constraints Between Classes 引入类间依赖和约束的图像层次分类深度主动学习

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3552667

Yanxue Wu;Min Wang;Fan Min;Qi Wang;Zhiheng Zhang;Haoyu Zhang;Xiangbing Zhou

{"title":"Deep Active Learning for Image Hierarchical Classification by Introducing Dependencies and Constraints Between Classes","authors":"Yanxue Wu;Min Wang;Fan Min;Qi Wang;Zhiheng Zhang;Haoyu Zhang;Xiangbing Zhou","doi":"10.1109/TSMC.2025.3552667","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3552667","url":null,"abstract":"Deep active learning (DeepAL) extends supervised deep learning to human-machine interactive scenarios with limited annotation budgets. Most existing DeepAL approaches for visual recognition fail to consider the intrinsic hierarchical structure and dependencies between labels. In this article, we propose a unified DeepAL framework for the aforementioned challenge, which fuses three tightly coupled techniques: 1) hierarchical dependency representation entropy (HDRE); 2) approximate class-balanced typical sampling (ACTS); and 3) local probability suppression loss. First, the HDRE provides the features of information entropy, interclass dependencies, and constraints effectively. It is used to determine the query priority of unlabeled samples. Second, the ACTS, embedded with the HDRE, is designed for querying, where the optimal sample query size of each class is derived. It excludes samples near the boundary by employing a well-designed hierarchical margin sampling. Third, the local probability suppression loss is a transfer-friendly loss function that enables the deep model to flatly fit data with a hierarchical structure. It compensates for hierarchical dependencies between classes using the local probability suppression constraint, modeling conditional and unconditional probabilities simultaneously. We conducted experiments on five public image datasets, and the results demonstrated the effectiveness of our approach.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4396-4409"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073329","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

An Effective Computing Cloud–Edge-Seamless System for Industrial Internet of Things 面向工业物联网的高效计算云边缘无缝系统

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3548099

Xinyi Xie;Houbing Song;Shaobo Zhang;Anfeng Liu

{"title":"An Effective Computing Cloud–Edge-Seamless System for Industrial Internet of Things","authors":"Xinyi Xie;Houbing Song;Shaobo Zhang;Anfeng Liu","doi":"10.1109/TSMC.2025.3548099","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3548099","url":null,"abstract":"Growth of computing capacity at edge drives edge computing as an efficient computing model, and cloud computing is considered as an indispensable computing model as various cloud services emerge. However, edge computing performs gracelessly in persistent tasks and the tasks requiring dispersed data, whereas cloud computing is often accompanied with high latency. To deal with more complex network scenarios, we fuse the two computing models and propose cloud-edge-seamless system (CESS) which enables all infrastructures to orchestrate data as services in a 5G/6G network, realizing infrastructure as a service (IaaS). In CESS, raw data is processed on intermediate processing devices (IPDs) before reaches the cloud. Thereafter, we proposed OBRI scheme to minimize processing and routing delay in which IPD can orchestrate data as a service if it is busy and handle data roughly if it is idle, thus reducing data volumes and total delay according to IPD congestion. Furthermore, there is still a large number of flows queuing on downstream IPDs, then NOB scheme is proposed to reduce delay further, in which IPD sends notice to upstream IPDs when congestion occurs to restrict them to orchestrate data only. Thus, the flow velocity slows down and more flows are orchestrated as services upstream, resulting greater delay reduction. Extensive experimental results show that the proposed CESS is immensely efficient. OBRI and NOB can effectively reduce delay, balance load, and improve quality of experience (QoE). In addition, NOB provides great flexibility and is extremely suitable to process delay-sensitive data.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4230-4243"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072894","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

A Novel Data-Driven DRNN-SMC Model for Redundant Manipulators 一种新的数据驱动的冗余机械手DRNN-SMC模型

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3550943

Min Yang;Yuxin Guo;Siying Zhu;Ning Tan;Bolin Liao;Hui Zhang

{"title":"A Novel Data-Driven DRNN-SMC Model for Redundant Manipulators","authors":"Min Yang;Yuxin Guo;Siying Zhu;Ning Tan;Bolin Liao;Hui Zhang","doi":"10.1109/TSMC.2025.3550943","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3550943","url":null,"abstract":"The robot industry is developing rapidly, and how to control the redundant manipulators precisely and effectively has become a new hot topic in industry’s development. In recent years, many scholars in the industry have also proposed various control methods. However, most of these methods are proposed assuming that the Jacobian matrix is known. Actually, in practical applications, the detailed information of Jacobian matrix is often not precisely known. Therefore, this article develops a novel data-driven recurrent neural network (RNN) model that can update the Jacobian matrix and joint angles. By defining two dynamic error functions, two RNN designed formulas are used to obtain a continuous RNN (CRNN) model. Subsequently, the CRNN model is discretized by using Euler forward formula, and a discrete RNN (DRNN) model is generated. Then, a classic sliding mode control (SMC) algorithm is introduced, and DRNN-SMC model is further proposed. Moreover, the corresponding rigorous mathematical derivation and proof are carried out. In addition, simulation tests are carried out by using the Kinova Gen2 manipulator, comparing the DRNN model and PD controller, as well as the DRNN-SMC model and DRNN model, validating the precision of the DRNN-SMC model. Additionally, practical experiments using the Kinova Gen3 manipulator are performed to showcase the applicability and versatility of the DRNN-SMC model.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4322-4333"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073232","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

Self-Determination Theory and Deep Reinforcement Learning for Personalized Energy Trading in Smart Grid 智能电网个性化能源交易的自我决定理论与深度强化学习

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3551667

Min Zhang;Frank Eliassen;Amir Taherkordi;Hans-Arno Jacobsen;Yushuai Li;Yan Zhang

{"title":"Self-Determination Theory and Deep Reinforcement Learning for Personalized Energy Trading in Smart Grid","authors":"Min Zhang;Frank Eliassen;Amir Taherkordi;Hans-Arno Jacobsen;Yushuai Li;Yan Zhang","doi":"10.1109/TSMC.2025.3551667","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3551667","url":null,"abstract":"The development of automated home energy management (HEM) and peer-to-peer energy trading mechanisms encourages a greater number of energy consumers to switch roles and become providers. To sustain this trend and maintain their long-term commitment to energy platforms, we face the challenge of aligning the primary psychological motivators of prosumers with our developed energy services. Most existing approaches target maximizing prosumer utility based on extrinsic benefits, such as economic rewards. However, the intrinsic motivations which are inherently satisfying for prosumers, have not been thoroughly analyzed. This article explores both extrinsic and intrinsic motivations of prosumers from a psychological perspective and addresses these within the technological field. Self-determination theory is adopted as a psychological framework to analyze prosumer behavior in energy systems. The study quantifies prosumers’ motivations and proposes a quality-of-energy-service measure to reflect individual preferences. Additionally, a leader-follower-based optimization framework is introduced, enabling individual prosumers to make optimal decisions regarding their energy management and trading strategies in a P2P energy market. The proposed system features a deep reinforcement learning agent as the leader, targeting optimal HEM solutions, while the follower aims to find the optimal trading strategy for prosumers in an auction-based P2P trading environment. Numerical results demonstrate that our proposed model outperforms baseline models.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4216-4229"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072893","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 Scheduling of a Hydrogen-Based Microgrid for an Industrial Park: A Reinforcement Learning Approach 工业园区氢基微电网优化调度：强化学习方法

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3551325

Wangli He;Chenhao Cai;Qing-Long Han;Xiangyun Qing;Wenli Du;Feng Qian

{"title":"Optimal Scheduling of a Hydrogen-Based Microgrid for an Industrial Park: A Reinforcement Learning Approach","authors":"Wangli He;Chenhao Cai;Qing-Long Han;Xiangyun Qing;Wenli Du;Feng Qian","doi":"10.1109/TSMC.2025.3551325","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3551325","url":null,"abstract":"Many industrial parks, which are connected to the main grid, have integrated renewable energy to reduce carbon emission for achieving the goal of Industry 5.0. However, the optimal scheduling is challenging due to fluctuations in renewable energy generation. Hydrogen, which plays an important role in the future development of the power grid in Industry 5.0, offers an attractive option to coordinate with the batteries. This work focuses on the day-ahead scheduling of a hydrogen-based microgrid for an industrial park. A day-ahead scheduling model is established by taking into consideration the detailed nonlinear energy conversion behavior of the electrolyzer and fuel cell, as well as the two-timescale property of a battery energy storage system (BESS) and the hydrogen system, including an electrolyzer, a hydrogen energy storage system (HESS), and a fuel cell. Note that the optimization problem is a mixed integer nonlinear programming, which is challenging to be solved. A novel multilearning rate reinforcement learning algorithm is proposed and its convergence is also proved based on two-timescale stochastic approximation theory. Simulation results, based on real-world traces in Belgium at a 15-min resolution, are presented, which shows that the proposed method has a higher reward, lower-operating costs and less computing time. It is also found that the shorter scheduling period for the BESS can lead to reduced operating costs by decreasing the required purchasing power and the renewable energy curtailment power.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4348-4361"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073234","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

Privacy-Preserving Diffusion Adaptive Learning With Nonzero-Mean Protection Noise 具有非零均值保护噪声的隐私保护扩散自适应学习

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3550524

Hongyu Han;Sheng Zhang;Guanghui Wen

引用次数: 0

Event-Triggered Generalized State Observer-Based Finite-Time Fault-Tolerant Control of Underwater Vehicles With Input Saturation 基于事件触发广义状态观测器的输入饱和水下航行器有限时间容错控制

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3550917

Nihad Ali;Zahoor Ahmed;Hongtian Chen;Weidong Zhang

{"title":"Event-Triggered Generalized State Observer-Based Finite-Time Fault-Tolerant Control of Underwater Vehicles With Input Saturation","authors":"Nihad Ali;Zahoor Ahmed;Hongtian Chen;Weidong Zhang","doi":"10.1109/TSMC.2025.3550917","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3550917","url":null,"abstract":"This article addresses a finite-time trajectory tracking control problem for autonomous underwater vehicles with parametric uncertainties, external disturbances, thruster faults, and saturation. First, considering the unpredictable oceanic environment with the thruster faults and model uncertainties, an event-triggered finite-time generalized extended state observer (ETFTGESO) is developed to estimate the synthetic failure and unmeasured velocities simultaneously. Triggered position data is used as feedback in the correction terms of ETFTGESO, which consequently reduces unnecessary communication or computational burden. The observer order is expanded by two additional states, which enhance the estimation accuracy. Then, a homogeneous output feedback controller is proposed to achieve finite-time stability of the vehicle. To improve the convergence rate of the position and velocity trajectories, the finite-time control law is updated by integrating a homogeneous integral sliding surface. Rigorous theoretical analysis verifies fast convergence, the influence of control parameters on bounded stable region, and accurate dynamic positioning. Finally, numerical simulations are carried out to demonstrate the superiority of the proposed control scheme.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4151-4162"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073433","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

Analysis on Fault Detectability of Boolean Control Networks: A Labeled Graph Approach 布尔控制网络故障可检测性分析：一种标记图方法

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3550368

Jiahao Wu;Yang Liu;Jianlong Qiu;Zheng-Guang Wu;Mahmoud Abdel-Aty

{"title":"Analysis on Fault Detectability of Boolean Control Networks: A Labeled Graph Approach","authors":"Jiahao Wu;Yang Liu;Jianlong Qiu;Zheng-Guang Wu;Mahmoud Abdel-Aty","doi":"10.1109/TSMC.2025.3550368","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3550368","url":null,"abstract":"In this article, fault detectability of Boolean control networks (BCNs) is analyzed via a labeled graph approach. First, matrix-based representations of nonfault BCNs and fault BCNs are constructed by using the semi-tensor product (STP) of matrices. Based on these matrix representations, labeled graphs are further developed for nonfault BCNs and fault BCNs, respectively. Then, the passive fault detectability (PFD) is solved by labeled graph of the nonfault BCN. Meanwhile, based on the labeled graphs of nonfault BCNs and fault BCNs, the active fault detectability (AFD) is further studied. By leveraging labeled graphs, two sufficient criteria for strong AFD and AFD can be derived without the need for iterative matrix calculations, thereby significantly reducing computational complexity. Furthermore, the corresponding necessary and sufficient criteria are further derived when these two sufficient criteria are invalid. Finally, a biological system for the lac operon in <inline-formula> <tex-math>$Escherichia~coli$ </tex-math></inline-formula> is elaborated to verify the effectiveness of obtained results.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4301-4308"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073230","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

Leader-Following Consensus of MASs With Input Constraints: A Time-Varying Dynamic Event-Triggered Approach 具有输入约束的群体领导-跟随共识：时变动态事件触发方法

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3552416

Meilin Li;Tieshan Li;Kai Zhang

引用次数: 0

Fault Detection for Discrete-Time Takagi-Sugeno Fuzzy Systems With Unmeasurable Premise Variable With L₂ – L∞/H∞ Mixed Observer and Zonotopic Analysis 基于L 2 - L∞/H∞混合观测器和分区分析的前提变量不可测离散时间Takagi-Sugeno模糊系统故障检测

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-04-01 DOI: 10.1109/TSMC.2025.3548095

Yi Li;Jiuxiang Dong

{"title":"Fault Detection for Discrete-Time Takagi-Sugeno Fuzzy Systems With Unmeasurable Premise Variable With L₂ – L∞/H∞ Mixed Observer and Zonotopic Analysis","authors":"Yi Li;Jiuxiang Dong","doi":"10.1109/TSMC.2025.3548095","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3548095","url":null,"abstract":"For complex fuzzy nonlinear systems, the set membership estimation technique is often applied to fault detection or safety monitoring by giving a guaranteed estimation of the state. The main difficulty affecting the accuracy of existing set membership estimation methods for fuzzy system is the inability to obtain accurate model information online due to the unmeasurable premise variables. Therefore, a fault detection method based on membership function dependent (MFD) <inline-formula> <tex-math>${mathcal {L}}_{2}-{mathcal {L}}_{infty }/{mathcal {H}}_{infty }$ </tex-math></inline-formula> mixed performance observer and zonotopic analysis is proposed for discrete fuzzy systems with unmeasurable premise variables. First, a novel MFD <inline-formula> <tex-math>${mathcal {L}}_{2}-{{mathcal {L}}}_{infty }/{{mathcal {H}}}_{infty }$ </tex-math></inline-formula> performance is proposed, which reduces the conservatism of the traditional approach and provides more freedom to design. Second, on the basis of the proposed performance, the design conditions for the fault detection observer adopting the T-N-L structure are given using fuzzy basis-dependent Lyapunov functions, taking into account the effect of imprecise premise variables. Further, the effects caused by disturbances in the error dynamics of the observer as well as imprecise premise variables are handled using zonotopic analysis. The estimation results of the states and outputs in zonotopic and interval forms are given and applied to fault detection. Finally, the simulation shows that the proposed method provides guaranteed estimation in the absence of system faults and facilitates rapid fault detection when the system is faulty.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 6","pages":"4115-4124"},"PeriodicalIF":8.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073434","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