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Training Robust Graph Completion Networks with Extremely Weak Supervision on Graphs with Incomplete Features and Structure 在具有不完全特征和结构的图上训练具有极弱监督的鲁棒图补全网络
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.125906
Chengxiang Lei;Sichao Fu;Qinmu Peng;Yiyang Zhang;Bin Zou;Xiao-Yuan Jing;Xinge You
{"title":"Training Robust Graph Completion Networks with Extremely Weak Supervision on Graphs with Incomplete Features and Structure","authors":"Chengxiang Lei;Sichao Fu;Qinmu Peng;Yiyang Zhang;Bin Zou;Xiao-Yuan Jing;Xinge You","doi":"10.1109/JAS.2025.125906","DOIUrl":"https://doi.org/10.1109/JAS.2025.125906","url":null,"abstract":"Graph neural networks (GNNs) often suffer from performance degradation due to the incompleteness of node features and structure relationships in the real world. Recently emerged graph completion learning (GCL) enhances the generalization of GNNs by reconstructing the missing node features or structure relationships. Nevertheless, these proposed GCL methods are supervised by a large number of labeled nodes, which limits their applications in extremely limited labeled nodes. Moreover, the existing GCL methods either focus on feature missing or structure missing tasks, and little effort was paid to more challenging scenarios where both node features and structure relationships are simultaneously missing. In this paper, a general GCL framework with the aid of multi-level contrast graph mask autoencoders (EWS-RGCN) is proposed to improve the generalization of GNNs guided by extremely weak supervision on graphs with features and structure missing. Specifically, to alleviate the mutual interference between missing node features and structure relationships caused by message passing of GNNs, we separate the feature and structure completion into two channels. Then, a multi-level contrastive loss is introduced to simultaneously maximize the mutual information between nodes from the encoding and decoding stage, which can discover more effective supervision information from the data itself for EWS-RGCN optimization, apart from label information. To further enhance the space consistency between reconstructed node features and structure relationships, the inter-channel information cooperation module is introduced to enhance the mutual learning of feature and structure completion channels. Extensive experiments on six benchmarks demonstrate the effectiveness of our EWS-RGCN.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1707-1720"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661678","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 Sensor Selection of Linear Quadratic Regulation with Unknown Sensor Noise Covariances 未知噪声协方差下线性二次调节的最优传感器选择
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.125915
Jinna Li;Xinru Wang;Xiangyu Meng;Frank L. Lewis
{"title":"Optimal Sensor Selection of Linear Quadratic Regulation with Unknown Sensor Noise Covariances","authors":"Jinna Li;Xinru Wang;Xiangyu Meng;Frank L. Lewis","doi":"10.1109/JAS.2025.125915","DOIUrl":"https://doi.org/10.1109/JAS.2025.125915","url":null,"abstract":"This paper addresses an optimal sensor selection problem under the framework of linear quadratic regulation. Unlike prior work on optimal sensor scheduling, we assume that the sensor noise covariance matrices are comparable but unknown. Then, the optimal sensor selection problem is formulated as finding an optimal policy of selecting a sensor from a set of sensors to minimize the expected quadratic performance of a linear system given the number of trials. An action value method from reinforcement learning is adopted for estimating the values of selections and making selection decisions based on the estimates. Several ways of balancing exploration and exploitation are presented and compared for efficacy. Numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithms.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1747-1754"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661563","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
Event-Triggered-Based Adaptive Practical Fixed-Time Tracking Control for Uncertain Nonlinear Systems With Unmeasurable States 状态不可测不确定非线性系统的事件触发自适应实用定时跟踪控制
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2026.11639364
Lei Liang;Xia Huang;Zhen Wang
{"title":"Event-Triggered-Based Adaptive Practical Fixed-Time Tracking Control for Uncertain Nonlinear Systems With Unmeasurable States","authors":"Lei Liang;Xia Huang;Zhen Wang","doi":"10.1109/JAS.2026.11639364","DOIUrl":"https://doi.org/10.1109/JAS.2026.11639364","url":null,"abstract":"In this paper, the problem of adaptive event-triggered (ET) fixed-time tracking control (FTTC) for a class of uncertain nonlinear systems (NSs) with partially unmeasurable states is investigated. An observer and a set of radial basis function neural networks (RBFNNs) are introduced to reconstruct the unmeasurable states and to approximate the unknown nonlinear functions, respectively. Moreover, in order to reduce the communication resource consumption, an ET mechanism with the relative threshold is adopted. The designed ET controller can ensure that the tracking error converges to a small neighborhood of the origin, all the signals of the closed-loop system are uniformly ultimately bounded (UUB), the settling time depends solely on the design parameters, and the Zeno behavior is successfully avoided. A practical example is given to verify the feasibility of the proposed method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1721-1730"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661609","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
Fixed-Time Fault-Tolerant Control for Small UUV With Dual-Layer Evolving Performance Boundary Under Full-State Constraints 全状态约束下具有双层演化性能边界的小型无人潜航器固定时间容错控制
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.125516
Hongtao Liang;Huiping Li;Junzhi Yu
{"title":"Fixed-Time Fault-Tolerant Control for Small UUV With Dual-Layer Evolving Performance Boundary Under Full-State Constraints","authors":"Hongtao Liang;Huiping Li;Junzhi Yu","doi":"10.1109/JAS.2025.125516","DOIUrl":"https://doi.org/10.1109/JAS.2025.125516","url":null,"abstract":"This letter investigates the fixed-time fault-tolerant control (FTC) problem for small unmanned underwater vehicles (UUVs) subject to the full-state error constraints involving position-layer and velocity-layer. First, a dual-level evolving performance boundary is devised by integrating the fixed-time performance functions and low-complexity error transformation techniques. This novel formulation converts the full-state constrained control issue into a dual-layer unconstrained stabilization, thus ensuring fixed-time convergence regardless of initial conditions. Subsequently, based on the fuzzy logic system (FLS) and barrier Lyapunov functions (BLF), a robust FTC scheme is derived to enforce full-state constraints within desired behavioral boundaries and achieve the robustness against dynamics uncertainties, external disturbances and actuator faults. Finally, it is proved that the closed-loop system is stable and state constraints are never violated. Simulations verify the effectiveness of the proposed scheme.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1767-1769"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11639366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661812","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
Visual-Based Flower Counting: Techniques and Applications 基于视觉的花卉计数：技术和应用
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2026.126050
Siyang Zang;Lei Shu;Ru Han;Xing Yang;Grzegorz Cielniak;Feiya Zhang
{"title":"Visual-Based Flower Counting: Techniques and Applications","authors":"Siyang Zang;Lei Shu;Ru Han;Xing Yang;Grzegorz Cielniak;Feiya Zhang","doi":"10.1109/JAS.2026.126050","DOIUrl":"https://doi.org/10.1109/JAS.2026.126050","url":null,"abstract":"With the rapid integration of modern information technologies into agriculture, smart agriculture enables increasingly precise phenotyping and yield prediction. Flower counting is a key phenological indicator; however, achieving high precision remains a significant challenge due to severe occlusion, density variations, and environmental variability (e.g., lighting/weather). Moreover, existing studies remain fragmented without a comprehensive synthesis. To bridge this fundamental research gap, we present the first systematic survey of computer-vision-based flower counting. In this work, we propose a novel taxonomy that categorizes methods into static (single-image) and dynamic (video/multi-view) paradigms and elucidates their evolutionary trajectory. Unlike conventional reviews, we conduct a multi-scale evaluation encompassing both horizontal (methodological evolution from traditional to deep learning) and vertical (cross-species and scene-condition) performance analyses. Crucially, we validate representative algorithms on deployed platforms-UAV and ground robots-through engineering case studies that quantify real-world trade-offs (e.g., height-accuracy and latency-robust-ness). Finally, we discuss prevailing limitations and propose future directions, including graph-based reasoning and AgriVerse inte-gration (i.e., agriculture-centric metaverse or digital twin ecosys-tems), establishing a foundational framework for both academic research and industrial deployment.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1536-1557"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661502","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
Security Control of Nonlinear Systems Subject to Deception Attacks: A Reinforcement Learning Approach 欺骗攻击下非线性系统的安全控制：一种强化学习方法
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.125513
Lifeng Ma;Yongyi Dai;Chen Gao
{"title":"Security Control of Nonlinear Systems Subject to Deception Attacks: A Reinforcement Learning Approach","authors":"Lifeng Ma;Yongyi Dai;Chen Gao","doi":"10.1109/JAS.2025.125513","DOIUrl":"https://doi.org/10.1109/JAS.2025.125513","url":null,"abstract":"Dear Editor, This letter deals with the security control for nonlinear cyber-physical systems (CPSs) under mixed deception attacks. Both sensors and actuators are assumed to be injected deception data during the data transmission via networks. In order to identify the unknown dynamics of the attacked system, a neural network (NN) is adopted, on basis of which an NN-based secure observer is designed to diminish the attack impact on state estimation. Then, by resorting to the reinforcement learning approach, the secure control strategy is presented via actor-critic and zero-sum games. At last, the designed control scheme is proved via a numerical simulation.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1764-1766"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11639373","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661702","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
A Hybrid Encoding-Based Coordinated Optimization Method for Charging Matrix Design in the Blast Furnace Ironmaking Process 基于混合编码的高炉炼铁过程装料矩阵协调优化设计方法
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.126011
Jicheng Zhu;Zhaohui Jiang;Dong Pan;Haoyang Yu;Chuan Xu;Ke Zhou;Weihua Gui
{"title":"A Hybrid Encoding-Based Coordinated Optimization Method for Charging Matrix Design in the Blast Furnace Ironmaking Process","authors":"Jicheng Zhu;Zhaohui Jiang;Dong Pan;Haoyang Yu;Chuan Xu;Ke Zhou;Weihua Gui","doi":"10.1109/JAS.2025.126011","DOIUrl":"https://doi.org/10.1109/JAS.2025.126011","url":null,"abstract":"A well-designed charging matrix (CM) is crucial for advancing green and low-carbon production in the blast furnace (BF) ironmaking process. Over recent years, metaheuristics algorithms have been applied to optimize CM, partially reducing reliance on on-site workers. However, CM optimization is a challenging mixed-variable constraint optimization problem. Prior studies predominantly simplify CM to either continuous or discrete forms via variable fixation or type conversion, which hinders the efficient joint optimization of heterogeneous variables, limiting optimization accuracy and search efficiency. To tackle this barrier, this study proposes a novel method named Hybrid Encoding-based Adaptive Coordinated Differential Evolution (HE-ACoDE), marking the first attempt to optimize CM from a mixed-variable perspective. First, a hybrid encoding scheme is devised to provide a unified representation for the mixed variables in CM. Then, a coordinated mixed-variable mutation strategy is developed, effectively facilitating the synchronized evolution of continuous and discrete variables. Moreover, a constraint-aware selection operator and a weight-guided parameter adaptation strategy are proposed, which collaboratively guide the population toward feasible, high-quality solutions across different evolutionary stages and problem landscapes. Extensive comparison experiments on two industrial scenarios demonstrate that HE-ACoDE outperforms state-of-the-art CM optimization and mixed-variable optimization methods in terms of accuracy, stability, and convergence performance.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1689-1706"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661791","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
Random Search Deep Neural Networks Driven Koopman Subspace Modeling of Nonlinear Dynamics 随机搜索深度神经网络驱动的非线性动力学Koopman子空间建模
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.125612
Zixiang Yuan;Jie Ding;Dezhi Shen;Min Xiao
{"title":"Random Search Deep Neural Networks Driven Koopman Subspace Modeling of Nonlinear Dynamics","authors":"Zixiang Yuan;Jie Ding;Dezhi Shen;Min Xiao","doi":"10.1109/JAS.2025.125612","DOIUrl":"https://doi.org/10.1109/JAS.2025.125612","url":null,"abstract":"Nonlinear dynamic system is difficult to model by traditional modeling methods, because of high nonlinearity and limited precision. Koopman operator, an effective technique, maps nonlinear dynamic systems to a higher-dimensional linear space, allowing complex non-linear behavior to be described linearly. However, conventional Koopman-based approaches often suffer from computational complexity, this paper employs a deep neural network with random search to learn feature mappings and estimates the Koopman operator by subspace identification. Experimental results show the approach simplifies modeling and significantly improves modeling accuracy over traditional methods.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1770-1772"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11639378","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661593","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
Fully Distributed Reinforcement Learning for Efficient Networked Microgrids Resource Management: Source-Load-Storage Coordination 高效网络微电网资源管理的全分布式强化学习：源-负载-存储协调
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.125636
Xiaowen Wang;Xinquan Shao;Shuai Liu
{"title":"Fully Distributed Reinforcement Learning for Efficient Networked Microgrids Resource Management: Source-Load-Storage Coordination","authors":"Xiaowen Wang;Xinquan Shao;Shuai Liu","doi":"10.1109/JAS.2025.125636","DOIUrl":"https://doi.org/10.1109/JAS.2025.125636","url":null,"abstract":"This letter proposes a fully distributed multi-agent reinforcement learning (DMARL) algorithm for the coordinated optimization and scheduling of source-load-storage in networked microgrids. To accommodate the rapid development of networked microgrids, we have designed a DMARL algorithm with an event-triggered mechanism (ETM). Unlike centralized approaches, DMARL empowers individual agents to cooperatively learn and optimize based only on local observations, while reducing the communication burden. Simulation results validate the performance of the proposed algorithm, demonstrating its effectiveness in efficient microgrid resource management.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1755-1757"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11639374","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661731","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
Intelligent Fault Diagnosis of Rolling Bearing With Variable Speed Based on ASTFrFT and Time-Frequency BoTNet Model 基于ASTFrFT和时频僵尸网络模型的变速滚动轴承故障智能诊断
IF 18.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-07-01 Epub Date: 2026-08-03 DOI: 10.1109/JAS.2025.125264
Jie Ma;Jun Wei;Xinyu Wang
{"title":"Intelligent Fault Diagnosis of Rolling Bearing With Variable Speed Based on ASTFrFT and Time-Frequency BoTNet Model","authors":"Jie Ma;Jun Wei;Xinyu Wang","doi":"10.1109/JAS.2025.125264","DOIUrl":"https://doi.org/10.1109/JAS.2025.125264","url":null,"abstract":"This letter presents an intelligent fault diagnosis method for variable speed rolling bearings based on the adaptive short-time fractional Fourier transform (ASTFrFT) and the time-frequency BoTNet (TFB) to address the challenge of extracting fault characteristics of rolling bearings under variable speed conditions and the poor classifi-cation of classical deep learning models. Firstly, to address the limitations of FrFT in time-varying signal processing, the physical mechanism of traditional STFT is extended into the FrFT domain by minimizing fuzzy entropy values to construct the order matrix. Subsequently, each signal segment undergoes rotation filtering to derive its time-frequency (TF) distribution. Finally, the resulting TF images are inputted into the TFB, which utilizes fully connected and classification layers to identify two-dimensional TF domain features for intelligent diagnosis automatically. Experimental validation and comparative studies confirm the effectiveness and superiority of the proposed method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 7","pages":"1761-1763"},"PeriodicalIF":18.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11639365","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661746","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
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