IEEE Transactions on Cybernetics最新文献_第9页

Event-Triggered Almost Output Regulation for Switched T-S Fuzzy Systems 切换T-S模糊系统的事件触发几乎输出调节。

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-20 DOI: 10.1109/TCYB.2025.3547288

Shuanghe Yu;Ying Zhao;Jingjie Xu

{"title":"Event-Triggered Almost Output Regulation for Switched T-S Fuzzy Systems","authors":"Shuanghe Yu;Ying Zhao;Jingjie Xu","doi":"10.1109/TCYB.2025.3547288","DOIUrl":"10.1109/TCYB.2025.3547288","url":null,"abstract":"This article investigates the event-triggered (ET) almost output regulation (ETAOR) issue for the switched T-S fuzzy (T-SF) systems with both output regulation (OR) characteristic and <inline-formula> <tex-math>$L_{2}$ </tex-math></inline-formula> gain characteristic considered. First, in order to conserve communication resources, an ET mechanism and an ET switched fuzzy feedback controller are devised. Then, the definition of the ETAOR issue for the switched T-SF systems is presented. Next, with the relaxed assumption of the same coordinate transformation, the ETAOR issue of the switched T-SF systems is transformed into the ET <inline-formula> <tex-math>$H_{infty } $ </tex-math></inline-formula> control problem of the switched T-SF systems. Further, by using the multiple Lyapunov functions approach, a solvability condition on the ETAOR issue is established for the switched T-SF systems with the average dwell-time related switching signals. Such condition is also suitable for nonswitched T-SF systems. In addition, Zeno behavior may be caused by the ET programme is excluded. Finally, the presented control method is applied to an aero-engine case study to corroborate its effectiveness.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2223-2233"},"PeriodicalIF":9.4,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669720","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 Scalable Test Problem Generator for Sequential Transfer Optimization 时序传输优化的可伸缩测试问题生成器。

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-20 DOI: 10.1109/TCYB.2025.3547565

Xiaoming Xue;Cuie Yang;Liang Feng;Kai Zhang;Linqi Song;Kay Chen Tan

{"title":"A Scalable Test Problem Generator for Sequential Transfer Optimization","authors":"Xiaoming Xue;Cuie Yang;Liang Feng;Kai Zhang;Linqi Song;Kay Chen Tan","doi":"10.1109/TCYB.2025.3547565","DOIUrl":"10.1109/TCYB.2025.3547565","url":null,"abstract":"Despite the increasing interest in sequential transfer optimization (STO), a comprehensive benchmark suite for systematically comparing various STO algorithms remains underexplored. Existing test problems, which are often manually configured and lack scalability, can result in biased and nongeneralizable algorithm performance. In light of the above, we first introduce four concepts for characterizing STO problems (STOPs) in this study and present an important feature, namely similarity distribution, to quantitatively delineate the relationship between the optimal solutions of source and target tasks. Subsequently, we present general design guidelines for STOPs and introduce a problem generator that demonstrates strong scalability. Specifically, the similarity distribution of a problem can be easily customized through a novel inverse generation strategy, allowing for a continuous spectrum that captures the diverse similarity relationships present in real-world scenarios. Lastly, a benchmark suite comprising 12 STOPs, characterized by a range of customized similarity relationships, has been developed using the proposed generator and will serve as a platform for examining various STO algorithms. For instance, biased transferability representation, irregular mapping learning behaviors, and performance improvements unrelated to search experience are significant empirical findings that previous benchmarks failed to reveal, yet can be effectively identified through our test problems. The source code of the proposed problem generator is available at <uri>https://github.com/XmingHsueh/STOP-G</uri>.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2110-2123"},"PeriodicalIF":9.4,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669711","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 State Space Model for Multiobject Full 3-D Information Estimation From RGB-D Images RGB-D图像多目标全三维信息估计的状态空间模型

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-19 DOI: 10.1109/TCYB.2025.3548788

Jiaming Zhou;Qing Zhu;Yaonan Wang;Mingtao Feng;Jian Liu;Jianan Huang;Ajmal Mian

{"title":"A State Space Model for Multiobject Full 3-D Information Estimation From RGB-D Images","authors":"Jiaming Zhou;Qing Zhu;Yaonan Wang;Mingtao Feng;Jian Liu;Jianan Huang;Ajmal Mian","doi":"10.1109/TCYB.2025.3548788","DOIUrl":"10.1109/TCYB.2025.3548788","url":null,"abstract":"Visual understanding of 3-D objects is essential for robotic manipulation, autonomous navigation, and augmented reality. However, existing methods struggle to perform this task efficiently and accurately in an end-to-end manner. We propose a single-shot method based on the state space model (SSM) to predict the full 3-D information (pose, size, shape) of multiple 3-D objects from a single RGB-D image in an end-to-end manner. Our method first encodes long-range semantic information from RGB and depth images separately and then combines them into an integrated latent representation that is processed by a modified SSM to infer the full 3-D information in two separate task heads within a unified model. A heatmap/detection head predicts object centers, and a 3-D information head predicts a matrix detailing the pose, size and latent code of shape for each detected object. We also propose a shape autoencoder based on the SSM, which learns canonical shape codes derived from a large database of 3-D point cloud shapes. The end-to-end framework, modified SSM block and SSM-based shape autoencoder form major contributions of this work. Our design includes different scan strategies tailored to different input data representations, such as RGB-D images and point clouds. Extensive evaluations on the REAL275, CAMERA25, and Wild6D datasets show that our method achieves state-of-the-art performance. On the large-scale Wild6D dataset, our model significantly outperforms the nearest competitor, achieving 2.6% and 5.1% improvements on the IOU-50 and 5°10 cm metrics, respectively.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2248-2260"},"PeriodicalIF":9.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661347","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 Subspace Search-Based Evolutionary Algorithm for Large-Scale Constrained Multiobjective Optimization and Application 一种基于子空间搜索的大规模约束多目标优化进化算法及其应用

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-19 DOI: 10.1109/TCYB.2025.3548414

Xuanxuan Ban;Jing Liang;Kunjie Yu;Kangjia Qiao;Ponnuthurai Nagaratnam Suganthan;Yaonan Wang

{"title":"A Subspace Search-Based Evolutionary Algorithm for Large-Scale Constrained Multiobjective Optimization and Application","authors":"Xuanxuan Ban;Jing Liang;Kunjie Yu;Kangjia Qiao;Ponnuthurai Nagaratnam Suganthan;Yaonan Wang","doi":"10.1109/TCYB.2025.3548414","DOIUrl":"10.1109/TCYB.2025.3548414","url":null,"abstract":"Large-scale constrained multiobjective optimization problems (LSCMOPs) exist widely in science and technology. LSCMOPs pose great challenges to algorithms due to the need to optimize multiple conflicting objectives and satisfy multiple constraints in a large search space. To better address such problems, this article proposes a dynamic subspace search-based evolutionary algorithm for solving LSCMOPs. The main idea is to initially allow the population to search in a low-dimensional subspace to increase convergence, then the searched subspace is gradually expanded to encourage the population to further search the full decision space. Specifically, the contribution of each decision variable to the evolution is first calculated using the proposed decision variable analysis method. Then, a probability-based offspring generation strategy is developed to encourage the population to preferentially search in a low-dimensional subspace composed of decision variables with high contribution degrees, thus speeding up the early convergence. With the continuous progress of evolution, the subspace is gradually expanded to ensure that the population can better explore the entire space. The performance of the proposed algorithm is evaluated on a variety of test problems with 100–1000 decision variables. Experimental results on four test suits and three real-world instances show that the proposed algorithm is efficient in solving LSCMOPs.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2486-2499"},"PeriodicalIF":9.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661348","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

Unsupervised Feature Selection for High-Order Embedding Learning and Sparse Learning 高阶嵌入学习和稀疏学习的无监督特征选择

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-19 DOI: 10.1109/TCYB.2025.3546658

Zebiao Hu;Jian Wang;Jacek Mańdziuk;Zhongxin Ren;Nikhil R. Pal

{"title":"Unsupervised Feature Selection for High-Order Embedding Learning and Sparse Learning","authors":"Zebiao Hu;Jian Wang;Jacek Mańdziuk;Zhongxin Ren;Nikhil R. Pal","doi":"10.1109/TCYB.2025.3546658","DOIUrl":"10.1109/TCYB.2025.3546658","url":null,"abstract":"The majority of the unsupervised feature selection methods usually explore the first-order similarity of the data while ignoring the high-order similarity of the instances, which makes it easy to construct a suboptimal similarity graph. Furthermore, such methods, often are not suitable for performing feature selection due to their high complexity, especially when the dimensionality of the data is high. To address the above issues, a novel method, termed as unsupervised feature selection for high-order embedding learning and sparse learning (UFSHS), is proposed to select useful features. More concretely, UFSHS first takes advantage of the high-order similarity of the original input to construct an optimal similarity graph that accurately reveals the essential geometric structure of high-dimensional data. Furthermore, it constructs a unified framework, integrating high-order embedding learning and sparse learning, to learn an appropriate projection matrix with row sparsity, which helps to select an optimal subset of features. Moreover, we design a novel alternative optimization method that provides different optimization strategies according to the relationship between the number of instances and the dimensionality, respectively, which significantly reduces the computational complexity of the model. Even more amazingly, the proposed optimization strategy is shown to be applicable to ridge regression, broad learning systems and fuzzy systems. Extensive experiments are conducted on nine public datasets to illustrate the superiority and efficiency of our UFSHS.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2355-2368"},"PeriodicalIF":9.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661503","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 Improved Topology Identification Method of Complex Dynamical Networks 一种改进的复杂动态网络拓扑识别方法

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-19 DOI: 10.1109/TCYB.2025.3547772

Yi Zheng;Xiaoqun Wu;Ziye Fan;Kebin Chen;Jinhu Lü

引用次数: 0

Feasible Policy Iteration With Guaranteed Safe Exploration 有保证安全探索的可行策略迭代。

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-18 DOI: 10.1109/TCYB.2025.3542223

Yuhang Zhang;Yujie Yang;Shengbo Eben Li;Yao Lyu;Jingliang Duan;Zhilong Zheng;Dezhao Zhang

{"title":"Feasible Policy Iteration With Guaranteed Safe Exploration","authors":"Yuhang Zhang;Yujie Yang;Shengbo Eben Li;Yao Lyu;Jingliang Duan;Zhilong Zheng;Dezhao Zhang","doi":"10.1109/TCYB.2025.3542223","DOIUrl":"10.1109/TCYB.2025.3542223","url":null,"abstract":"Safety guarantee is an important topic when training real-world tasks with reinforcement learning (RL). During online environmental exploration, any constraint violation can lead to significant property damage and risks to personnel. Existing safe RL methods either exclusively address safety concerns after reaching optimality or incorporate a certain degree of tolerance for constraint violations during training. This article proposes a feasible policy iteration framework that can guarantee absolute safety during online exploration, i.e., constraint violations never happen in real-world interactions. The key to maintaining absolute safety lies in confining the environmental exploration at each step always within the feasible region of the current policy. This feasible region is described by a newly defined constraint decay function with uncertainty, ensuring the forward invariance of the feasible region under the worst case. Within the proposed framework, the feasible region maintains its monotonic expanding property and converges to its maximum extent, even though only local samples are available, i.e., the agent only has access to samples within the feasible region. Meanwhile, the trained policy also improves monotonically within its corresponding feasible region if one can use different updating rules inside and outside the feasible region. Finally, practical algorithms are designed with the actor-critic-scenery architecture, consisting of three modules: 1) safe exploration; 2) model error estimation; and 3) network update. Experimental results indicate that our algorithms achieve performance comparable to baselines while maintaining zero constraint violation throughout the entire training process. In contrast, the baseline algorithm typically requires thousands of constraint violations to achieve the same performance. These findings suggest a substantial potential for applying feasible policy iteration in real-world tasks, enabling the online evolution of intricate systems.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2327-2340"},"PeriodicalIF":9.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657070","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

Predictor-Based Feedback Control for Discrete-Time Time-Variant Linear State-Delayed Systems With Distinct Input Delays via State Transition Matrices 基于状态转移矩阵的离散时变线性时滞系统的预测反馈控制。

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-18 DOI: 10.1109/TCYB.2025.3542998

Ai-Guo Wu;Jie Zhang;Shi-Long Shen

引用次数: 0

Finite-Time Stabilizers for Large-Scale Stochastic Boolean Networks 大规模随机布尔网络的有限时间稳定器。

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-18 DOI: 10.1109/TCYB.2025.3545689

Lin Lin;James Lam;Wai-Ki Ching;Qian Qiu;Liangjie Sun;Bo Min

{"title":"Finite-Time Stabilizers for Large-Scale Stochastic Boolean Networks","authors":"Lin Lin;James Lam;Wai-Ki Ching;Qian Qiu;Liangjie Sun;Bo Min","doi":"10.1109/TCYB.2025.3545689","DOIUrl":"10.1109/TCYB.2025.3545689","url":null,"abstract":"This article presents a distributed pinning control strategy aimed at achieving global stabilization of Markovian jump Boolean control networks. The strategy relies on network matrix information to choose controlled nodes and adopts the algebraic state space representation approach for designing pinning controllers. Initially, a sufficient criterion is established to verify the global stability of a given Markovian jump Boolean network (MJBN) with probability one at a specific state within finite time. To stabilize an unstable MJBN at a predetermined state, the selection of pinned nodes involves removing the minimal number of entries, ensuring that the network matrix transforms into a strictly lower (or upper) triangular form. For each pinned node, two types of state feedback controllers are developed: 1) mode-dependent and 2) mode-independent, with a focus on designing a minimally updating controller. The choice of controller type is determined by the feasibility condition of the mode-dependent pinning controller, which is articulated through the solvability of matrix equations. Finally, the theoretical results are illustrated by studying the T cell large granular lymphocyte survival signaling network consisting of 54 genes and 6 stimuli.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2098-2109"},"PeriodicalIF":9.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657078","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

Resilient Distributed Nash Equilibrium Control for Nonlinear MASs Under DoS Attacks DoS攻击下非线性质量的弹性分布式纳什均衡控制。

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-18 DOI: 10.1109/TCYB.2025.3543675

Shihan Zhou;Chao Deng;Sha Fan;Bohui Wang;Wei-Wei Che

{"title":"Resilient Distributed Nash Equilibrium Control for Nonlinear MASs Under DoS Attacks","authors":"Shihan Zhou;Chao Deng;Sha Fan;Bohui Wang;Wei-Wei Che","doi":"10.1109/TCYB.2025.3543675","DOIUrl":"10.1109/TCYB.2025.3543675","url":null,"abstract":"This article investigates the resilient distributed Nash equilibrium (NE) control problem for nonlinear multiagent systems (MASs) that suffers from denial-of-service (DoS) attacks in the communication network. Different from the existing works on NE seeking in noncooperative games, it is the first trial to consider the resilient distributed NE control problem for nonlinear MASs under DoS attacks. To overcome the challenges caused by the considered problem, a new layered NE control method is developed, which consists of a resilient distributed NE seeking algorithm, two-stage cascade filters, and a resilient adaptive controller. Specifically, the resilient distributed NE seeking algorithm is proposed to ensure that the actions in this algorithm converge to the NE even under DoS attacks. Then, the improved actions with smooth characteristics are designed by introducing novel two-stage cascade filters. By using newly designed actions and their derivatives, a resilient adaptive controller is proposed to ensure that the output of MASs converges to the NE. Finally, simulation results are provided to verify the effectiveness of the proposed strategy.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"2316-2326"},"PeriodicalIF":9.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657090","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