IEEE Transactions on Cybernetics最新文献_第3页

Finite-Time Fractional-Order Control for Multiagent Formation System Based on Switching Function: Application to UAV/UGV. 基于切换函数的多智能体编队系统有限时间分数阶控制：在无人机/UGV中的应用。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-24 DOI: 10.1109/tcyb.2026.3684893

Shuyi Shao,Guangxin Jiao,Mou Chen,Qingyun Yang

引用次数: 0

H ∞ Optimal Tracking Control for Two-Time-Scale Supply Chain Systems Subject to DoS Attack. DoS攻击下双时间尺度供应链系统的H∞最优跟踪控制。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-24 DOI: 10.1109/tcyb.2026.3684433

Qing-Kui Li,Hong-Kai Yang,Hai Lin,Wei He

{"title":"H ∞ Optimal Tracking Control for Two-Time-Scale Supply Chain Systems Subject to DoS Attack.","authors":"Qing-Kui Li,Hong-Kai Yang,Hai Lin,Wei He","doi":"10.1109/tcyb.2026.3684433","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3684433","url":null,"abstract":"This article investigates the $H_{infty }$ optimal tracking control problem for supply chain systems characterized by two distinct time scales and vulnerability to denial-of-service (DoS) attacks. To reduce the computational complexity and eliminate the sensitivity to time-scale variations inherent in traditional lifting techniques, the system is decomposed into fast and slow subsystems using singular perturbation theory. A policy iteration (PI)-based $H_{infty }$ optimal control scheme is proposed to attenuate the bullwhip effect in supply chain systems, namely, the amplification of customer demand uncertainty throughout the network. The control scheme allows inventory levels to accurately track desired targets even in the presence of perturbations. To address the information loss caused by DoS attacks, a nonlinear autoregressive (NAR) neural network-based predictor is designed to provide real-time state compensation. The method's effectiveness is validated through a case study of a potassium carbonate production process. Simulation results demonstrate that the proposed approach reduces the bullwhip effect by 63% and provides superior steady-state accuracy and dynamic performance compared with the existing integral sliding-mode and standard policy-iteration methods.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"115 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147739042","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

Internal Temperature Estimation of Pouch-Type Lithium-Ion Battery by a 2-D Semilinear PDE Model With Space-Dependent Diffusivity. 基于空间相关扩散系数的二维半线性PDE模型估算袋式锂离子电池内部温度。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-24 DOI: 10.1109/tcyb.2026.3683396

Fudong Ge,YangQuan Chen,Zhiqiang Zuo

引用次数: 0

Recent Advances on Off-Policy Reinforcement Learning for Optimization Control. 非策略强化学习优化控制研究进展。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-23 DOI: 10.1109/tcyb.2026.3683384

Biao Luo,Derong Liu,Huai-Ning Wu,Tingwen Huang,Chunhua Yang,Weihua Gui

{"title":"Recent Advances on Off-Policy Reinforcement Learning for Optimization Control.","authors":"Biao Luo,Derong Liu,Huai-Ning Wu,Tingwen Huang,Chunhua Yang,Weihua Gui","doi":"10.1109/tcyb.2026.3683384","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3683384","url":null,"abstract":"Reinforcement learning (RL), a key artificial intelligence technique, has been widely studied and applied over the past two decades to solve various optimization control problems. Generally speaking, there are two basic frameworks for RL-based control design, i.e., on-policy and off-policy RL (OffP-RL). The essential distinction between the two frameworks lies in whether the policy used to generate training data is the behavior policy or the target policy. In on-policy RL-based control methods, the data used for evaluating the target control policy at each iteration must be collected from the system under the target policy itself. In contrast, in OffP-RL methods, the system data is generated by other behavior control policies. It addresses the inadequate exploration problem in on-policy RL methods, making OffP-RL methods more practical and easier to implement. In this article, the recent advances in OffP-RL-based control methods are classified into three categories based on the number of controllers/players involved, i.e., single-/two-/multiplayer. For the single-player case, it is an optimal control problem, which aims to use OffP-RL to learn the optimal control policy, which minimizes the performance index. In the two-player case, most works focus on the $H_{infty } $ control problem and the two-player zero-sum game, using learning to find the Nash equilibrium. In the multiplayer case, a multiplayer game involves a single system with multiple control inputs, while a multiagent system consists of multiple systems with independent control inputs. Finally, related applications of OffP-RL-based control and future work are analyzed.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"118 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147735444","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

Prescribed-Time Output-Feedback Tracking Control of a Class of Time-Varying Output-Constrained Systems. 一类时变输出约束系统的规定时间输出反馈跟踪控制。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-23 DOI: 10.1109/tcyb.2026.3684456

Di Jiang,Feng Zhang,Bin Zhou,Huaiyuan Jiang

引用次数: 0

Reparameterization-Driven Depthwise Separable Large-Kernel Network for Lightweight Salient Object Detection of Strip Steel Surface Defects. 基于重参数化驱动的深度可分离大核网络的轻量显著目标检测。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-22 DOI: 10.1109/tcyb.2026.3684146

Xiaofei Zhou,Zhenkun Mo,Gongyang Li,Liuxin Bao,Xiaobin Xu,Jiyong Zhang

{"title":"Reparameterization-Driven Depthwise Separable Large-Kernel Network for Lightweight Salient Object Detection of Strip Steel Surface Defects.","authors":"Xiaofei Zhou,Zhenkun Mo,Gongyang Li,Liuxin Bao,Xiaobin Xu,Jiyong Zhang","doi":"10.1109/tcyb.2026.3684146","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3684146","url":null,"abstract":"With the rapid development of neural networks, strip steel surface defect detection, as an important task in computer vision, has achieved remarkable progress. However, state-of-the-art methods still face a tradeoff between accuracy and efficiency. High-performing models are usually large and computationally expensive, whereas lightweight models often suffer from limited detection accuracy. To address this issue, we first propose a spatial channel enhancement (SCE) module, which consists of a reparameterizable depthwise large-kernel convolution and a reparameterizable pointwise (RepPw) convolution. The proposed SCE module enlarges the receptive field and strengthens long-range spatial and channel interactions while preserving computational efficiency. Based on the SCE module, we propose a novel lightweight saliency model for strip steel surface defects, namely, reparameterization-driven depthwise separable large-kernel network (RepDSLKNet). RepDSLKNet employs SCE modules to build an encoder and a decoder, and utilizes cascaded channel attention (CCA) modules for the feature fusion. The lightweight architecture can effectively extract and fuse the semantic information and detailed features of strip steel surface defects, thereby improving the accuracy and speed of detection with a small model size. With an input size of $224times 224$ , our RepDSLKNet has only 0.47 M parameters and 0.42 G FLOPs during inference. Compared to the current state-of-the-art methods, our approach achieves a 19-fold improvement in throughput and a twofold reduction in latency. Experiments on two public strip steel defect datasets demonstrate that RepDSLKNet delivers competitive performance against state-of-the-art methods.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"144 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147733986","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

Prescribed-Performance Control of Variable-Order Fractional-Order Nonlinear Systems Through Adaptive Dynamic Programming. 基于自适应动态规划的变阶分数阶非线性系统规定性能控制。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-21 DOI: 10.1109/tcyb.2026.3681504

Jie Kong,Hansong Li,Bo Zhao,Cesare Alippi

{"title":"Prescribed-Performance Control of Variable-Order Fractional-Order Nonlinear Systems Through Adaptive Dynamic Programming.","authors":"Jie Kong,Hansong Li,Bo Zhao,Cesare Alippi","doi":"10.1109/tcyb.2026.3681504","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3681504","url":null,"abstract":"This article investigates the prescribed-performance control (P2C) of variable-order fractional-order nonlinear systems (VOFONSs) through a control barrier function (CBF)-embedded adaptive dynamic programming (ADP) method. Owing to the time dependence and the global memory characteristics of the variable-order fractional calculus, the existing analysis methods for traditional integer-order systems cannot be directly applied. By using the variable-order fractional calculus and the integration-by-parts formula, the VOFONS is approximately transformed into a time-varying integer-order nonlinear system. To address the P2C problem, a prescribed-performance function is designed to reformulate the P2C problem as a constrained control problem of the time-varying integer-order nonlinear system. Unlike conventional function transformation-based methods, the proposed CBF-embedded ADP control method incorporates the safety constraints into the ADP-based optimal control framework without requiring explicit state transformation. Since the constructed discounted cost function is time-varying due to the involvement of time-varying CBF, it is approximated by a neural network with a time-varying activation function. Then, a time-varying policy iteration algorithm is developed to solve the Hamilton-Jacobi-Bellman (HJB) equation. Hereafter, the CBF-based control policy is derived to guarantee that the tracking error satisfies the predefined constraint. Simulation results verify the effectiveness of the present CBF-embedded ADP control scheme.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"21 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147731499","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 Fault-Tolerant Control for Wastewater Treatment Processes With Asymmetric State Constraints. 非对称状态约束下污水处理过程的定时容错控制。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-21 DOI: 10.1109/tcyb.2026.3683543

Hong-Gui Han,Han-Qian Hou,Hao-Yuan Sun,Jun-Fei Qiao

引用次数: 0

Cross-Dimensional Fault-Tolerant Control of Heterogeneous Fully Actuated Multiagent Systems Against Hybrid Faults 异构全驱动多智能体系统对混合故障的跨维容错控制

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-04-20 DOI: 10.1109/tcyb.2026.3681627

Yonghao Ma, Ke Zhang, Bin Jiang

引用次数: 0

A Novel Approach for Adaptive Tracking Control of Nonlinear Systems Subject to Long-Range-Dependent Stochastic Disturbances 一种具有长期相关随机扰动的非线性系统自适应跟踪控制方法