Pub Date : 2026-01-12DOI: 10.1109/tcyb.2025.3650634
Haoen Huang, Wei He, Zhigang Zeng
{"title":"An Integral-Enhanced Adaptive Gradient Neural Network for k WTA and Multirobot Coordination","authors":"Haoen Huang, Wei He, Zhigang Zeng","doi":"10.1109/tcyb.2025.3650634","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3650634","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"25 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955713","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}
Pub Date : 2026-01-12DOI: 10.1109/tcyb.2025.3649615
Xueyan Yan, Xun-Lin Zhu, Jumei Wei, Xiangjun Xia, Haiping Du
{"title":"Frequent Asynchronous Switching of Networked Switched Systems Under Event-Triggered Fault-Tolerant Control and DoS Attacks","authors":"Xueyan Yan, Xun-Lin Zhu, Jumei Wei, Xiangjun Xia, Haiping Du","doi":"10.1109/tcyb.2025.3649615","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3649615","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"45 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955714","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}
Pub Date : 2026-01-12DOI: 10.1109/tcyb.2025.3649685
Zeyi Liu, Weihua Gui, Keke Huang, Dehao Wu, Chunhua Yang
{"title":"A Diffusion-Based Unified Framework for Open-World Dynamic Wheel Recognition System Construction and Maintenance With Incomplete Data","authors":"Zeyi Liu, Weihua Gui, Keke Huang, Dehao Wu, Chunhua Yang","doi":"10.1109/tcyb.2025.3649685","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3649685","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"50 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955706","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}
Pub Date : 2026-01-12DOI: 10.1109/tcyb.2025.3650460
Archit Krishna Kamath, Mir Feroskhan
{"title":"Physics-Embedded Networks: Improving Convergence and Precision of Physics-Informed Neural Networks for Real-Time Applications","authors":"Archit Krishna Kamath, Mir Feroskhan","doi":"10.1109/tcyb.2025.3650460","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3650460","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"146 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955711","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}
This article addresses the problem of distributed state estimation (DSE) for discrete-time interconnected systems, where the observed system is composed of subsystems interconnected through state-to-state and state-to-output couplings. Inspired by the leader-follower consensus method, we propose a distributed observer that enables each subsystem to estimate the entire state of the interconnected system. Under certain structural assumptions, we derive necessary and sufficient conditions for the stability of the estimation error dynamics. We further present a decentralized design of the proposed observer, where the operation and construction of the observer can be completed by each subsystem using its locally available information, including the system's basic configuration, local measurements, and data exchanged with neighboring subsystems. In addition, we demonstrate that our distributed estimation framework can be applied to solve the distributed estimation problem for linear time-invariant (LTI) systems with fixed composition by employing an observability decomposition method. Finally, we illustrate the effectiveness of our scheme by applying it to vehicle platooning.
{"title":"A Decentralized Designed Distributed Observer for Linear Interconnected Systems.","authors":"Shuaiting Huang,Lingying Huang,Peng Yi,Hong Chen,Guodong Shi,Junfeng Wu","doi":"10.1109/tcyb.2025.3647742","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3647742","url":null,"abstract":"This article addresses the problem of distributed state estimation (DSE) for discrete-time interconnected systems, where the observed system is composed of subsystems interconnected through state-to-state and state-to-output couplings. Inspired by the leader-follower consensus method, we propose a distributed observer that enables each subsystem to estimate the entire state of the interconnected system. Under certain structural assumptions, we derive necessary and sufficient conditions for the stability of the estimation error dynamics. We further present a decentralized design of the proposed observer, where the operation and construction of the observer can be completed by each subsystem using its locally available information, including the system's basic configuration, local measurements, and data exchanged with neighboring subsystems. In addition, we demonstrate that our distributed estimation framework can be applied to solve the distributed estimation problem for linear time-invariant (LTI) systems with fixed composition by employing an observability decomposition method. Finally, we illustrate the effectiveness of our scheme by applying it to vehicle platooning.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"82 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907598","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}
Pub Date : 2026-01-06DOI: 10.1109/tcyb.2025.3646012
Zhichuang Wang,Wei He,Jian Sun,Gang Wang
This article addresses the switching law design problem for switched nonlinear time-delay systems (SNTDSs). The existing switching laws, such as dwell time, average dwell time (ADT), and mode-dependent ADT (MDADT), depict the switching frequency by linear functions of switching interval length, which may insufficiently characterize the switching numbers and features of SNTDSs. To effectively ensure the system stability of SNTDSs and relax the conservatism of stability criteria, two novel switching laws, average switching density and mode-dependent average switching density (MDASD), are first proposed to illustrate the switching frequency of SNTDSs. Meanwhile, under the new switching laws, by constructing the proper multiple Lyapunov-Razumikhin functions, relaxed integral inequalities, and the trajectory-based approach, stability criteria are presented for SNTDSs, which can encompass and include certain aspects of prior research. Moreover, we apply the new switching laws and theoretical results to switched neural networks. Ultimately, we present two examples to confirm the effectiveness of the approaches we have developed.
{"title":"Novel Switching Laws for Switched Nonlinear Time-Delay Systems and Applications to Neural Networks.","authors":"Zhichuang Wang,Wei He,Jian Sun,Gang Wang","doi":"10.1109/tcyb.2025.3646012","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3646012","url":null,"abstract":"This article addresses the switching law design problem for switched nonlinear time-delay systems (SNTDSs). The existing switching laws, such as dwell time, average dwell time (ADT), and mode-dependent ADT (MDADT), depict the switching frequency by linear functions of switching interval length, which may insufficiently characterize the switching numbers and features of SNTDSs. To effectively ensure the system stability of SNTDSs and relax the conservatism of stability criteria, two novel switching laws, average switching density and mode-dependent average switching density (MDASD), are first proposed to illustrate the switching frequency of SNTDSs. Meanwhile, under the new switching laws, by constructing the proper multiple Lyapunov-Razumikhin functions, relaxed integral inequalities, and the trajectory-based approach, stability criteria are presented for SNTDSs, which can encompass and include certain aspects of prior research. Moreover, we apply the new switching laws and theoretical results to switched neural networks. Ultimately, we present two examples to confirm the effectiveness of the approaches we have developed.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"42 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907601","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}
The coal mine integrated energy system dispatch problem (CMIES-DP) is a constrained multiobjective optimization problem (CMOP) with the characteristics of multiple objectives, high-dimensional decision variables, and multiple constraints, which makes it challenging for existing methods. On the one hand, existing constrained multiobjective evolutionary algorithms (CMOEAs) are prone to falling into local optima when facing problems with high-dimensional variables. On the other hand, the relationship between objectives and constraints of CMIES-DP has not been fully analyzed to guide the design of targeted solving techniques. Therefore, this article proposes a time-division-based CMOEA (TDCEA), where the characteristics of CMIES-DP are analyzed to design two main strategies. First, by analyzing the temporal relationship of objectives and constraints, CMIES-DP is decomposed into multiple subproblems with fewer variables and constraints, and these subproblems are sequentially solved to obtain better decision variables. Then, a random concatenation method is designed to combine the decision variables output from subproblems into a solution set with complete decision variables, and the new solution set will be further optimized to find feasible Pareto optimal solutions. Second, the relationship between constraints and objectives is analyzed to guide the design of evolving populations, so as to improve the search ability of the algorithm. In the experiments, the proposed algorithm is used to solve a real-world CMIES-DP case, and results demonstrate that compared with other advanced algorithms, the proposed algorithm achieves better performance regarding diversity, convergence, and distribution.
{"title":"A Time-Division-Based Constrained Multiobjective Optimization Method for Coal Mine Integrated Energy System Dispatch Problem.","authors":"Kangjia Qiao,Jing Liang,Dunwei Gong,Yong Zhang,Canyun Dai,Jun Ma,Xuanxuan Ban,Kunjie Yu","doi":"10.1109/tcyb.2025.3649862","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3649862","url":null,"abstract":"The coal mine integrated energy system dispatch problem (CMIES-DP) is a constrained multiobjective optimization problem (CMOP) with the characteristics of multiple objectives, high-dimensional decision variables, and multiple constraints, which makes it challenging for existing methods. On the one hand, existing constrained multiobjective evolutionary algorithms (CMOEAs) are prone to falling into local optima when facing problems with high-dimensional variables. On the other hand, the relationship between objectives and constraints of CMIES-DP has not been fully analyzed to guide the design of targeted solving techniques. Therefore, this article proposes a time-division-based CMOEA (TDCEA), where the characteristics of CMIES-DP are analyzed to design two main strategies. First, by analyzing the temporal relationship of objectives and constraints, CMIES-DP is decomposed into multiple subproblems with fewer variables and constraints, and these subproblems are sequentially solved to obtain better decision variables. Then, a random concatenation method is designed to combine the decision variables output from subproblems into a solution set with complete decision variables, and the new solution set will be further optimized to find feasible Pareto optimal solutions. Second, the relationship between constraints and objectives is analyzed to guide the design of evolving populations, so as to improve the search ability of the algorithm. In the experiments, the proposed algorithm is used to solve a real-world CMIES-DP case, and results demonstrate that compared with other advanced algorithms, the proposed algorithm achieves better performance regarding diversity, convergence, and distribution.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"15 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907599","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}
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