IEEE Transactions on Systems Man Cybernetics-Systems最新文献

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Reinforcement Dynamic Learning-Based Tracking Control Strategy for an Unknown 2-DOF Helicopter System 未知二自由度直升机系统基于强化动态学习的跟踪控制策略
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-18 DOI: 10.1109/TSMC.2025.3582830
Weitian He;Fukai Zhang;Zhijia Zhao;Chenguang Yang;Cong Wang
{"title":"Reinforcement Dynamic Learning-Based Tracking Control Strategy for an Unknown 2-DOF Helicopter System","authors":"Weitian He;Fukai Zhang;Zhijia Zhao;Chenguang Yang;Cong Wang","doi":"10.1109/TSMC.2025.3582830","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3582830","url":null,"abstract":"This study investigates a multitrajectory tracking control strategy for an unknown 2-DOF helicopter system, integrating deterministic learning (DL) and reinforcement learning (RL). Initially, DL theory is applied to identify the local unknown dynamics of a 2-DOF helicopter system using radial basis function neural networks (RBFNNs). Subsequently, the identified dynamic knowledge is expressed and stored using constant RBFNNs. To mitigate the issue of partial knowledge failure due to deviations between the actual and learned trajectories, we introduce a RL framework for dynamic compensation. Finally, a composite control strategy incorporating both nominal and auxiliary components is designed to achieve multitrajectory tracking control. The stability of the closed-loop system is analyzed and demonstrated using the Lyapunov direct method. The simulation and experimental results demonstrate the effectiveness of the proposed control strategy.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"6777-6788"},"PeriodicalIF":8.7,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100473","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
TechRxiv: Share Your Preprint Research With the World! techxiv:与世界分享你的预印本研究!
IF 8.6 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-18 DOI: 10.1109/TSMC.2025.3584580
{"title":"TechRxiv: Share Your Preprint Research With the World!","authors":"","doi":"10.1109/TSMC.2025.3584580","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3584580","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 8","pages":"5773-5773"},"PeriodicalIF":8.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11085021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
IEEE Transactions on Systems, Man, and Cybernetics: Systems Publication Information IEEE系统、人与控制论汇刊:系统出版信息
IF 8.6 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-18 DOI: 10.1109/TSMC.2025.3584484
{"title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems Publication Information","authors":"","doi":"10.1109/TSMC.2025.3584484","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3584484","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 8","pages":"C2-C2"},"PeriodicalIF":8.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11085009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors IEEE系统、人与控制论汇刊:作者的系统信息
IF 8.6 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-18 DOI: 10.1109/TSMC.2025.3584488
{"title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors","authors":"","doi":"10.1109/TSMC.2025.3584488","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3584488","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 8","pages":"C4-C4"},"PeriodicalIF":8.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11085012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Switching Fixed-Time Control for Interconnected Nonlinear Systems With Unknown Control Directions and Unmodeled Dynamics 具有未知控制方向和未建模动力学的互联非线性系统的切换定时控制
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-18 DOI: 10.1109/TSMC.2025.3584772
Wei Tian;Changchun Hua;Kuo Li;Pengju Ning
{"title":"Switching Fixed-Time Control for Interconnected Nonlinear Systems With Unknown Control Directions and Unmodeled Dynamics","authors":"Wei Tian;Changchun Hua;Kuo Li;Pengju Ning","doi":"10.1109/TSMC.2025.3584772","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3584772","url":null,"abstract":"This article investigates the fixed-time control problem for a class of uncertain p-normal interconnected nonlinear systems with output constraints. Different from the existing fixed-time control results, unmodeled dynamics are allowed in the system model and the unknown control coefficients under consideration are time varying with nonidentical signs. To deal with this challenge, by applying the adding a power integrator method, a decentralized adaptive controller is built with a switching parameter to compensate unknown parameters. Based on fixed-time control framework, a logic-based switching rule is established to tune the switching parameter online, in which the Lyapunov-like boundary functions are utilized to replace the Lyapunov function containing inexact values brought by unmodeled dynamics. Then, with the aid of Lyapunov stability theorem, it is proved that the system output never violates the prespecified constraints and all state variables converge to zero within a fixed time. Finally, the validity of the presented method is demonstrated by a numerical simulation.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"6802-6813"},"PeriodicalIF":8.7,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100408","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
IEEE Systems, Man, and Cybernetics Society Information IEEE系统、人与控制论学会信息
IF 8.6 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-18 DOI: 10.1109/TSMC.2025.3584494
{"title":"IEEE Systems, Man, and Cybernetics Society Information","authors":"","doi":"10.1109/TSMC.2025.3584494","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3584494","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 8","pages":"C3-C3"},"PeriodicalIF":8.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11085020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors IEEE系统、人与控制论汇刊:作者的系统信息
IF 8.6 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-18 DOI: 10.1109/TSMC.2025.3584576
{"title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors","authors":"","doi":"10.1109/TSMC.2025.3584576","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3584576","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 8","pages":"C4-C4"},"PeriodicalIF":8.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11085010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Neural Networks-Incorporated Latent Factor Analysis for High-Dimensional and Incomplete Data 基于神经网络的高维不完全数据潜在因素分析
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-16 DOI: 10.1109/TSMC.2025.3583919
Mingwei Lin;Xingyu Lin;Xiuqin Xu;Zeshui Xu;Xin Luo
{"title":"Neural Networks-Incorporated Latent Factor Analysis for High-Dimensional and Incomplete Data","authors":"Mingwei Lin;Xingyu Lin;Xiuqin Xu;Zeshui Xu;Xin Luo","doi":"10.1109/TSMC.2025.3583919","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3583919","url":null,"abstract":"high-dimensional and incomplete (HDI) matrices are commonly encountered in a variety of big data-related industrial applications, which describe complex interactions between entities. The complete interaction relationship in the HDI matrix is essential to deal with various problems such as pattern recognition in industrial applications. Therefore, estimating the missing data in the HDI matrix is crucial. latent factor analysis (LFA) models have achieved advanced results in solving such problems. However, the existing LFA models cannot model the nonlinear structure hidden in the HDI matrix. neural networks (NNs) can handle the nonlinearity in the HDI data, but their high estimation accuracy relies on high computation cost and storage burden. To address the aforementioned problems, this article proposes a novel NNLFA model. It contains the following primary ideas: 1) it can model the nonlinear structure of the HDI matrix efficiently through NNs and 2) it incorporates the NNs into the LFA model to improve estimation accuracy while maintaining high computational and storage efficiency. To validate the superiority of the NNLFA model, experiments with six state-of-the-art models are conducted on six practical industrial application datasets. The experimental results indicate that the NNLFA model enhances estimation accuracy by up to 33.3%. In addition, NNLFA model shows strong competitiveness in terms of both time and storage efficiency when compared to baseline models.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7302-7314"},"PeriodicalIF":8.7,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090075","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
Adaptive Event-Triggered Optimal Control With Regulative Learning Rate Under Aperiodic DoS Attacks 非周期DoS攻击下具有调节学习率的自适应事件触发最优控制
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-16 DOI: 10.1109/TSMC.2025.3583832
Chushu Yi;Yongqing Yang;Jinde Cao
{"title":"Adaptive Event-Triggered Optimal Control With Regulative Learning Rate Under Aperiodic DoS Attacks","authors":"Chushu Yi;Yongqing Yang;Jinde Cao","doi":"10.1109/TSMC.2025.3583832","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3583832","url":null,"abstract":"In this article, the optimal control for a nonlinear affine system under aperiodic Denial-of-service (DoS) attacks is investigated. To solve the Hamilton–Jacobi–Bellman (HJB) equation, an adaptive dynamic programming (ADP) algorithm based on a single critic network is developed. The proposed regulative learning rate strategy outperforms traditional fixed-rate gradient descent approaches found in existing works. With the objective of minimizing the performance index, the optimal value function and the optimal controller are derived from the approximate solution of the HJB equation. To alleviate the resource demand and enhance the flexibility of the threshold function, an adaptive event-triggered (AET) scheme integrating the idea of sampling control and event-triggered strategy is applied to the optimal control initially. Compared with the static event-triggered strategy, the AET method contains increasing engineering value. A piecewise Lyapunov function is constructed based on optimal value function, estimated error introduced by neural network (NN) weight, and the classic Lyapunov-Krasovskii function. Thus, uniform ultimate boundedness for tracking error is proven theoretically. Moreover, the maximum tolerable strength of cyberattacks is provided from the stability analysis. The simulation results exhibit the designed approach’s reliability.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7024-7036"},"PeriodicalIF":8.7,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100440","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
Adaptive Robust Motion Control for Hydraulic Actuators With an Adjustable Event Trigger 带有可调事件触发器的液压执行器的自适应鲁棒运动控制
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-15 DOI: 10.1109/TSMC.2025.3581240
Jixiang Chen;Zhongyang Fei;Litong Lyu;Weiguo Xia;Xi-Ming Sun
{"title":"Adaptive Robust Motion Control for Hydraulic Actuators With an Adjustable Event Trigger","authors":"Jixiang Chen;Zhongyang Fei;Litong Lyu;Weiguo Xia;Xi-Ming Sun","doi":"10.1109/TSMC.2025.3581240","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3581240","url":null,"abstract":"This article investigates the event-triggered adaptive robust motion control for hydraulic actuators with parametric uncertainties and system nonlinearities. Under the continuous communication condition, the traditional adaptive robust motion controller is recursively presented. In order to reduce the unnecessary bandwidth consumption in the aero-engine networked control platform, an adaptive threshold triggered mechanism according to network resources is developed to synthesize the motion controller. Adjustable threshold parameters are involved to flexibly adjust the data transmission times depending on the network bandwidth occupation. It is proved that with the motion controller and the proposed adjustable threshold triggered mechanism, all the closed-loop system signals are globally bounded, and the hydraulic system output achieves asymptotic tracking to the reference trajectory by virtue of the adaptive technique, the Nussbaum-type and sign functions. Besides, the Zeno behavior is excluded, successfully. Finally, the proposed event-based control scheme is tested and discussed on the aero-engine hardware-in-the-loop (HIL) experiment platform with hydraulic actuators.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7205-7214"},"PeriodicalIF":8.7,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100434","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
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