{"title":"Distributed Adaptive Tracking Control for Fuzzy Nonlinear MASs Under Round-Robin Protocol","authors":"Sha Fan, Min Meng, Yukai Fu, Chao Deng","doi":"10.1109/tfuzz.2025.3525989","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525989","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"25 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142934570","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}
{"title":"Dynamic Fuzzy Sampler for Graph Neural Networks","authors":"Jia Wei;Xingjun Zhang;Witold Pedrycz;Weiping Ding","doi":"10.1109/TFUZZ.2024.3509018","DOIUrl":"10.1109/TFUZZ.2024.3509018","url":null,"abstract":"Graph Neural Networks (GNNs) are widely used across fields, with inductive learning replacing transductive learning as the mainstream training paradigm due to its superior memory efficiency, computation speed, and generalization. Neighbor node sampling, a key step in inductive learning, is critical to model performance. However, existing samplers focus only on adjacency matrix-based sampling, neglecting the varying impacts of different neighbors on target nodes over time. They usually aggregate the neighbor information in a simple way such as averaging or summing, which limits the information representation, robustness, and generalization. To address these limitations, we propose a Dynamic Fuzzy Sampler (DFS) based on a Gaussian fuzzy system. DFS accounts for node diversity and models the uncertainties and fuzziness in neighbor-target mutual information dynamically. Specifically, DFS first innovatively constructs a learnable Gaussian fuzzy set system for determining the membership degree of different neighbors to the target node at different moments. Subsequently, DFS aggregates the target node embeddings and membership-weighted neighbor embeddings to update the target node's features, which makes the target node utilize the sampling information more effectively. The aggregated target node effectively captures the graph structure information and neighbor node information, which can facilitate the subsequent graph neural network-based graph representation model with stronger representation and generalization capabilities. Experimental results on supervised and self-supervised graph datasets demonstrate that DFS consistently outperforms state-of-the-art sampling schemes. DFS achieves up to 1.90% and 9.52% F1-score improvement compared to the state-of-the-art schemes on small- and large-scale graphs, respectively.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 4","pages":"1357-1368"},"PeriodicalIF":10.7,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142934629","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}
{"title":"Event-Triggered Trajectory Tracking Control for Unmanned Surface Vessels With Prescribed Performance Using Barrier Lyapunov Functions","authors":"Xian Du, Xu Yuan, Bin Yang, Xudong Zhao","doi":"10.1109/tfuzz.2025.3525701","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525701","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"159 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142924716","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}
{"title":"Small-Gain-Based Fixed-Time Faulty Parameter Estimation for the Interconnected Fuzzy Systems With Multiple Time-Varying Delays","authors":"Ke Zhang;Qingyi Liu;Bin Jiang","doi":"10.1109/TFUZZ.2024.3520347","DOIUrl":"10.1109/TFUZZ.2024.3520347","url":null,"abstract":"This article investigates the fixed-time faulty parameter estimation problem for an interconnected fuzzy system with multiple time-varying delays. Based on the persistent excitation condition, an adaptive observer with a faulty parameter identification algorithm is constructed, to provide the accurate information of partial loss of actuator effectiveness within a fixed settling-time, and to guarantee the boundedness of state estimation error by mitigating the influence of external disturbance. Accordingly, several sufficient conditions for the existence of fuzzy observer gain, and the convergence proof of the input-to-state stability are also presented by utilizing the small-gain technique. Afterwards, an active fault-tolerant controller is synthesized to maintain the faulty interconnected system by compensating the actuator fault. Finally, simulation results on an inverted-pendulum system and a numerical example show the feasibility and advantage of the proposed approaches.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 4","pages":"1343-1356"},"PeriodicalIF":10.7,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142924731","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}
{"title":"Secure Control for T-S Fuzzy Wind Turbine Systems Under Hybrid Cyberattacks Via an Adaptive Memory Event-Triggered Mechanism","authors":"Dong Xu, Yajuan Liu, Sangmoon Lee","doi":"10.1109/tfuzz.2025.3525778","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525778","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"8 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142924717","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}
Zhibin Zhu, Yunbiao Jiang, Zhongxin Liu, Fuyong Wang
{"title":"Fuzzy Adaptive Group Formation-Containment Tracking Control of Nonlinear Multiagent Systems With Intermittent Actuator Faults","authors":"Zhibin Zhu, Yunbiao Jiang, Zhongxin Liu, Fuyong Wang","doi":"10.1109/tfuzz.2025.3525481","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525481","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"6 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142917152","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}
{"title":"Fuzzy Quantum Group Decision Making and Its Application in Meteorological Disaster Emergency","authors":"Shuli Yan, Yizhao Xu, Zaiwu Gong, Enrique Herrera-Viedma","doi":"10.1109/tfuzz.2024.3525009","DOIUrl":"https://doi.org/10.1109/tfuzz.2024.3525009","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"72 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142917153","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}
{"title":"Predefined-Time Fuzzy Formation Control for High-Order Multiagent Systems via Event-Triggered Schemes","authors":"Jiawei Ma;Huaguang Zhang;Juan Zhang;Lei Wan","doi":"10.1109/TFUZZ.2024.3524716","DOIUrl":"10.1109/TFUZZ.2024.3524716","url":null,"abstract":"This research considers the predefined-time adaptive fuzzy formation control issue for high-order nonlinear multiagent systems. By applying fuzzy logic systems, the systems unknown nonlinear functions can be approximated. To refrain from “explosion of complexity problem”, a novel dynamics surface for high-order nonlinear multiagent systems is presented. Further, to minimize the communication burden, an event-triggered mechanism suitable for high-order nonlinear multiagent systems is applied in the control methods. With the help of the backstepping design scheme and the adding power integral method, an adaptive fuzzy predefined-time formation control approach is proposed so that all signals in the considered systems are bounded and realize the desired formation control within predefined time. The illustrative examples are presented to verify the validity of the suggested method.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 4","pages":"1333-1342"},"PeriodicalIF":10.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142911798","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}