IEEE Transactions on Systems Man Cybernetics-Systems最新文献_第6页

Disturbance Observer-Based Neural Network Control of a 2-DOF Helicopter System With Input Saturation and Output Constraints

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-24 DOI: 10.1109/TSMC.2025.3538990

Zhijia Zhao;Di Zhang;Jiale Wu;Zhijie Liu;Min Wang;Keum-Shik Hong

引用次数: 0

Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-24 DOI: 10.1109/TSMC.2025.3539707

Weisheng Liang;Abdelhakim Amer;Mohit Mehndiratta;Zheng Chen;Bin Yao;Erdal Kayacan

{"title":"Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance","authors":"Weisheng Liang;Abdelhakim Amer;Mohit Mehndiratta;Zheng Chen;Bin Yao;Erdal Kayacan","doi":"10.1109/TSMC.2025.3539707","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3539707","url":null,"abstract":"With increasingly challenging applications for quadrotors, higher requirements are emerging for tracking accuracy and safety. While high accuracy is a prerequisite for complex tasks, safety is ensured through tolerance to actuator faults and resistance to external disturbances. In this article, adaptive robust control (ARC) integrated with Gaussian processes (GPs), i.e., ARC-GP, is proposed to achieve enhanced accuracy, fault tolerance, and anti-disturbance. These three requirements are interrelated and affected by uncertainties. The primary idea of this article is to categorize uncertainties into parametric and nonparametric types, which are then addressed through parameter adaptation and GP, respectively. First, a detailed dynamic model is established, including actuator models that reflect different types of faults corresponding to changes in different physical parameters. Then, parameter adaptation is designed, with direct and indirect methods adopted for different parameters. In particular, the actuator parameters are effectively estimated to achieve targeted fault compensation. Regarding GP for nonparametric uncertainties, its model parameters are also updated via parameter adaptation. The GP thereby also learns parameter estimation errors along with external disturbances. Accordingly, ARC controllers are designed, for which robust feedback terms are constructed to further mitigate uncertainties on the basis of the covariances predicted by GP. The experiments demonstrate that the proposed ARC-GP can actively tolerate various types of actuator faults and better resist wind disturbances.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3235-3248"},"PeriodicalIF":8.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839935","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

Distributed Nonconvex Optimal Resource Allocation via a Momentum-Based Multiagent Optimization Approach 通过基于动量的多代理优化方法实现分布式非凸优化资源分配

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-24 DOI: 10.1109/TSMC.2025.3539232

Zicong Xia;Wenwu Yu;Jinhu Lü

引用次数: 0

Neural Adaptive Boundary Control for Switched PDE Systems With Application to Chip Temperature Control

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-24 DOI: 10.1109/TSMC.2025.3540168

Xiaona Song;Zenglong Peng;Choon Ki Ahn;Shuai Song

引用次数: 0

Resilient Finite-Time Consensus of Variable-Order Fractional Multiagent Systems Under DoS Attacks DoS 攻击下变序分数多代理系统的弹性有限时间共识

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-21 DOI: 10.1109/TSMC.2025.3539656

Ruihong Li;Qintao Gan;Huaiqin Wu;Jinde Cao;Qiaokun Kang

{"title":"Resilient Finite-Time Consensus of Variable-Order Fractional Multiagent Systems Under DoS Attacks","authors":"Ruihong Li;Qintao Gan;Huaiqin Wu;Jinde Cao;Qiaokun Kang","doi":"10.1109/TSMC.2025.3539656","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3539656","url":null,"abstract":"This article aims to address the finite-time consensus issue for variable-order fractional multiagent systems (MASs) under denial of serve (DoS) attacks. First, the framework of node-based DoS attack is introduced, including its influences, detection, and recovery mechanisms. Second, a new variable-order fractional difference (VO-FD) inequality is proposed to accurately evaluate the variable-order fractional derivative of the power function. Based on the developed inequality, two novel finite-time stability theorems are presented based on the developed inequality, which fill up the gap in variable-order fractional finite-time stability without and with DoS attacks, respectively. Third, a resilient distributed control protocol is proposed, where the dynamic event-triggered mechanism (DETM) is introduced based on the detected signal of attack to ensure the desired control performance and economize system resources. According to the Lyapunov stability theory, the consensus can be achieved within the settling time, and some linear matrix inequality (LMI)-based conditions are obtained. Finally, the feasibility and validity of theoretical analysis is illustrated by simulation example.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3188-3201"},"PeriodicalIF":8.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840058","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 Control for Fractional Order Nonlinear Systems Based on Adaptive Dynamic Programming 基于自适应动态编程的分数阶非线性系统优化控制

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-21 DOI: 10.1109/TSMC.2024.3520962

Yuqing Yan;Huaguang Zhang;Jiayue Sun;Shuhang Yu

{"title":"Optimal Control for Fractional Order Nonlinear Systems Based on Adaptive Dynamic Programming","authors":"Yuqing Yan;Huaguang Zhang;Jiayue Sun;Shuhang Yu","doi":"10.1109/TSMC.2024.3520962","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3520962","url":null,"abstract":"In this article, an adaptive dynamic programming (ADP)-based optimal control strategy for a series of fractional-order nonlinear systems (FONS) with unknown control directions is investigated. To eliminate the challenges posed by unknown control directions, fractional-order Nussbaum-type functions are introduced for FONS, expanding the range of possible applications. Additionally, since system performance is compromised by disturbances, a fractional-order disturbance observer is designed to counteract the effects of external disturbances and enhance system robustness. Furthermore, differential geometric methods are employed to investigate FONS, constructing appropriate diffeomorphism that provide equivalent systems for decoupled linearization. Then, an optimal control method is studied for a class of strictly feedback FONS, in which Nussbaum-type functions are combined with ADP theory during the backstepping design process. Finally, based on fractional Lyapunov stability theory and backstepping method, it is guaranteed that all signals of the closed-loop FONS are uniformly ultimately bounded (UUB). Numerical simulation and a PMSM model are utilized to verify the effectiveness of the presented method.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3086-3097"},"PeriodicalIF":8.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839937","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

Wavelet-Infused Convolution-Transformer for Efficient Segmentation in Medical Images

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-21 DOI: 10.1109/TSMC.2025.3539573

Pallabi Dutta;Sushmita Mitra;Swalpa K. Roy

{"title":"Wavelet-Infused Convolution-Transformer for Efficient Segmentation in Medical Images","authors":"Pallabi Dutta;Sushmita Mitra;Swalpa K. Roy","doi":"10.1109/TSMC.2025.3539573","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3539573","url":null,"abstract":"Recent medical image segmentation methods extract the characteristics of anatomical structures only from the spatial domain, ignoring the distinctive patterns present in the spectral representation. This study aims to develop a novel segmentation architecture that leverages both spatial and spectral characteristics for better segmentation outcomes. This research introduces the wavelet-infused convolutional Transformer (WaveCoformer), a computationally effective framework to fuse information from both spatial and spectral domains of medical images. Fine-grained textural features are captured from the wavelet components by the convolution module. A transformer block identifies the relevant activation maps within the volumes, followed by self-attention to effectively learn long-range dependencies to capture the global context of the target regions. A cross-attention mechanism effectively combines the distinctive features acquired by both modules to produce a comprehensive and robust representation of the input data. WaveCoformer outperforms related state-of-the-art networks in publicly available Synapse and Adrenal tumor segmentation datasets, with a mean Dice score of 83.86% and 79%, respectively. The model is feasible for deployment in resource-constrained environments with rapid medical image analysis due to its computationally efficient nature and improved segmentation performance. The code is available at: <uri>https://github.com/duttapallabi2907/WaveCoformer</uri>.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3326-3337"},"PeriodicalIF":8.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839825","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

Deep Co-Training Partial Least Squares Model for Semi-Supervised Industrial Soft Sensing

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-21 DOI: 10.1109/TSMC.2025.3540028

Junhua Zheng;Le Zhou;Lingjian Ye;Zhiqiang Ge

{"title":"Deep Co-Training Partial Least Squares Model for Semi-Supervised Industrial Soft Sensing","authors":"Junhua Zheng;Le Zhou;Lingjian Ye;Zhiqiang Ge","doi":"10.1109/TSMC.2025.3540028","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540028","url":null,"abstract":"Data-driven soft sensing has become quite popular in recent years, which can provide real-time estimations of key variables in industrial processes. While the introduction of deep learning does improve the prediction performance, it is highly restricted to the number of labeled training data, as well as large computational burden and cumbersome parameter tuning procedures. How to break through the bottleneck of data-drive models in terms of limited labeled data and high computational complexity should be one of the main recent focuses in the field of industrial soft sensing. In this article, a deep co-training PLS (deep CT-PLS) model is proposed to extend the ordinary PLS model to the semi-supervised deep form. While the deep model can efficiently extract inherent natures of process data, the co-training strategy makes lots of unlabeled data useful through a two-view cross training and annotation process. In this case, the performance restriction of the deep PLS model can be greatly relieved, with the incorporation of additional unlabeled data, while at the same time the designed model structure keeps in a low computational complexity. Based on the case study on a real industrial production process, the deep CT-PLS model can significantly improve the soft sensing performance.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3363-3371"},"PeriodicalIF":8.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839930","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

Data-Driven Aperiodic Sampled-Data Control of Markovian Jump System

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-21 DOI: 10.1109/TSMC.2025.3540568

Guoliang Chen;Linqi Wang;Jianwei Xia;Xiangpeng Xie;Ju H. Park

引用次数: 0

Neuroadaptive Containment Control for Nonlinear Multiagent Systems With Input Saturation: An Event-Triggered Communication Approach 输入饱和非线性多代理系统的神经自适应遏制控制：一种事件触发通信方法

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-21 DOI: 10.1109/TSMC.2025.3540580

Xin Wang;Sen Zhang;Huaqing Li;Wei Zhang;Hongyi Li;Tingwen Huang

{"title":"Neuroadaptive Containment Control for Nonlinear Multiagent Systems With Input Saturation: An Event-Triggered Communication Approach","authors":"Xin Wang;Sen Zhang;Huaqing Li;Wei Zhang;Hongyi Li;Tingwen Huang","doi":"10.1109/TSMC.2025.3540580","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540580","url":null,"abstract":"In this article, a neuroadaptive event-triggered containment control strategy combined with the dynamic surface control (DSC) approach is proposed for nonlinear multiagent systems (MASs) with input saturation. Based on the event-triggered communication mechanisms, the updates of neural network weight and controllers are implemented solely under triggering conditions of violation, which markedly reduces unnecessary communication resources and minimizes inefficient control costs compared with the traditional control method. Radial basis function neural networks (RBF NNs) are employed to handle the nonlinear uncertainties of MASs. Simultaneously, an adaptive compensatory mechanism is incorporated within the backstepping process to address the nonlinear effect posed by input saturation. Additionally, we demonstrate the system stability by extending the Lyapunov theorem to jump and continuous scenarios while excluding Zeno behavior, realizing that all followers can enter the convex hull constructed by leaders. Finally, the effectiveness of the proposed methodology is verified through application simulations.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3163-3173"},"PeriodicalIF":8.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840056","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