Ieee-Caa Journal of Automatica Sinica最新文献_第8页

Development and Control of an Upper-Limb Exoskeleton CASIA-EXO for Motor Learning in Post-Stroke Rehabilitation 脑卒中后运动学习的上肢外骨骼CASIA-EXO的开发与控制

IF 19.2 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2024.124662

Chen Wang;Liang Peng;Zeng-Guang Hou

引用次数: 0

Camera Planning for Physical Safety of Outdoor Electronic Devices: Perspective and Analysis 户外电子设备物理安全的相机规划：观点与分析

IF 19.2 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2025.125129

Qin Su;Lei Shu;Gerhard Petrus Hancke;Kai Huang;Edmond Nurellari;Qingsong Zhao;Nikumani Choudhury;Anakhi Hazarika

{"title":"Camera Planning for Physical Safety of Outdoor Electronic Devices: Perspective and Analysis","authors":"Qin Su;Lei Shu;Gerhard Petrus Hancke;Kai Huang;Edmond Nurellari;Qingsong Zhao;Nikumani Choudhury;Anakhi Hazarika","doi":"10.1109/JAS.2025.125129","DOIUrl":"https://doi.org/10.1109/JAS.2025.125129","url":null,"abstract":"Camera technology advancement and deployment continue to play a vital role in modern life and production, amongst other capabilities, generating relevant visual information. The challenge of optimizing the use and deployment of camera networks in various applications (e.g., surveillance, traffic monitoring, and public safety to name but just a few) has attracted considerable attention from both academia and industries. Camera planning is the first step in addressing this challenge. The surveillance objectives and scenes of a camera network dictate the modelling and optimization algorithms for camera planning. However, existing reviews have primarily focused on models or optimization algorithms, with insufficient attention given to surveillance scenes. This review aims to bridge this gap by 1) Classifying surveillance scenes into the urban environment and rural outdoor environment and comparing the surveillance requirements and challenges; 2) Summarizing the details of camera coverage optimization in the relevant literature from the perspective of deployment scenes; and 3) Proposing a new surveillance scene —Solar Insecticidal Lamps with the Internet of Things—as a case study to analyze the surveillance requirement and challenges in agricultural outdoor environment. Finally, we state the technical outlook on the physical safety of outdoor electronic devices in agriculture settings and provide insights to draw more attention and effort into this area.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 8","pages":"1530-1543"},"PeriodicalIF":19.2,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880530","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

A Homotopy Method for Continuous-Time Model-Free LQR Control Based on Policy Iteration 基于策略迭代的连续时间无模型LQR控制同伦方法

IF 19.2 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2025.125132

Wenwu Fan;Junlin Xiong

引用次数: 0

Necessary and Sufficient Conditions for Controllability and Essential Controllability of Directed Circle and Tree Graphs 有向圆图和树图的可控性和本质可控性的充分必要条件

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2024.124866

Jijun Qu;Zhijian Ji;Jirong Wang;Yungang Liu

引用次数: 0

An Emulation Approach to Semi-Global Robust Output Regulation for a Class of Nonlinear Uncertain Systems 一类非线性不确定系统半全局鲁棒输出调节的仿真方法

IF 19.2 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2024.125085

Jieshuai Wu;Maobin Lu;Fang Deng;Jie Chen

{"title":"An Emulation Approach to Semi-Global Robust Output Regulation for a Class of Nonlinear Uncertain Systems","authors":"Jieshuai Wu;Maobin Lu;Fang Deng;Jie Chen","doi":"10.1109/JAS.2024.125085","DOIUrl":"https://doi.org/10.1109/JAS.2024.125085","url":null,"abstract":"In this paper, we investigate the semi-global robust output regulation problem of a class of nonlinear networked control systems. By the emulation approach, we propose a class of sampled-data output feedback control laws to solve this problem. In particular, we first develop a general sampled-data dynamic output feedback control law and characterize the closed-loop system by a hybrid system. Then, we design the internal model based on the sampled error output of the system. Based on the internal model principle, we convert the semi-global robust output regulation problem into a semi-global robust stabilization problem of an augmented hybrid system composed of the internal model and the original system. By proposing the sampled error output feedback control law and by means of Lyapunov analysis, we obtain the maximum allowable transmission interval for sampling and show that semi-global robust stabilization of the augmented hybrid system can be achieved by the proposed sampled-data control law and thus leading to the solution of the semi-global robust output regulation problem. Finally, we apply the proposed control approach to two practical applications to verify the effectiveness of the proposed control approach.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 8","pages":"1713-1723"},"PeriodicalIF":19.2,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880487","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

An Intelligent Optimization Strategy for Blast Furnace Charging Operation Considering Three-Dimensional Burden Surface Shape 考虑三维料面形状的高炉装料操作智能优化策略

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2025.125192

Jicheng Zhu;Zhaohui Jiang;Dong Pan;Haoyang Yu;Chuan Xu;Ke Zhou;Weihua Gui

{"title":"An Intelligent Optimization Strategy for Blast Furnace Charging Operation Considering Three-Dimensional Burden Surface Shape","authors":"Jicheng Zhu;Zhaohui Jiang;Dong Pan;Haoyang Yu;Chuan Xu;Ke Zhou;Weihua Gui","doi":"10.1109/JAS.2025.125192","DOIUrl":"https://doi.org/10.1109/JAS.2025.125192","url":null,"abstract":"Today, a well-devised charging operation scheme is urgently needed by on-site workmen and is critical for building an intelligent blast furnace (BF). Previous research on charging operations always focused on the two-dimensional shape of the burden surface (i.e., a single radial profile) while neglecting the unique feature of global dissymmetry, severely restricting the development of precise charging. For this reason, this study proposes an innovative optimization strategy for the charging operation under the three-dimensional burden surface, which is the first attempt in this field. First, a practicable region partitioning scheme is introduced, and the partitioning results are then integrated with the charging mechanism to construct a three-dimensional burden surface prediction model. Next, the intrinsic relationship between the operational parameters and charging volume is revealed based on the law of mass conservation, which forms the basis for defining a novel operational parameter with variable-speed utility, referred to as the neotype charging matrix (NCM). To find the best NCM, a customized NCM optimization strategy, involving a dual constraint handling technique in conjunction with a two-stage hybrid variable differential evolution algorithm, is further developed. The industrial experiment results manifest that the partitioning scheme significantly enhances the accuracy of burden surface description. Moreover, the NCM optimization strategy offers greater flexibility and higher accuracy than current mainstream optimization strategies for the charging matrix (CM).","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 7","pages":"1445-1463"},"PeriodicalIF":15.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536528","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

Instance by Instance: An Iterative Framework for Multi-Instance 3D Registration 实例-实例：多实例3D注册的迭代框架

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2024.125058

Jiaqi Yang;Xinyue Cao;Xiyu Zhang;Yuxin Cheng;Zhaoshuai Qi;Siwen Quan

{"title":"Instance by Instance: An Iterative Framework for Multi-Instance 3D Registration","authors":"Jiaqi Yang;Xinyue Cao;Xiyu Zhang;Yuxin Cheng;Zhaoshuai Qi;Siwen Quan","doi":"10.1109/JAS.2024.125058","DOIUrl":"https://doi.org/10.1109/JAS.2024.125058","url":null,"abstract":"Multi-instance registration is a challenging problem in computer vision and robotics, where multiple instances of an object need to be registered in a standard coordinate system. Pioneers followed a non-extensible one-shot framework, which prioritizes the registration of simple and isolated instances, often struggling to accurately register challenging or occluded instances. To address these challenges, we propose the first iterative framework for multi-instance 3D registration (MI-3DReg) in this work, termed instance-by-instance (IBI). It successively registers instances while systematically reducing outliers, starting from the easiest and progressing to more challenging ones. This enhances the likelihood of effectively registering instances that may have been initially overlooked, allowing for successful registration in subsequent iterations. Under the IBI framework, we further propose a sparse-to-dense correspondence-based multi-instance registration method (IBI-S2DC) to enhance the robustness of MI-3DReg. Experiments on both synthetic and real datasets have demonstrated the effectiveness of IBI and suggested the new state-of-the-art performance with IBI-S2DC, e.g., our mean registration F1 score is 12.02%/12.35% higher than the existing state-of-the-art on the synthetic/real datasets. The source codes are available online at https://github.com/caoxy01/IBI.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 6","pages":"1117-1128"},"PeriodicalIF":15.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281243","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 Adaptive Horizon DMPC for Discrete-Time Coupled Nonlinear Systems 离散时间耦合非线性系统的事件触发自适应水平DMPC

IF 19.2 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-07 DOI: 10.1109/JAS.2024.124704

Rui Guo;Jianwen Feng;Jingyi Wang;Yi Zhao

引用次数: 0

Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects 基于涡流检测的多尺度时间序列分割网络检测表面金属缺陷

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-04 DOI: 10.1109/JAS.2025.125117

Xiaorui Li;Xiaojuan Ban;Haoran Qiao;Zhaolin Yuan;Hong-Ning Dai;Chao Yao;Yu Guo;Mohammad S. Obaidat;George Q. Huang

{"title":"Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects","authors":"Xiaorui Li;Xiaojuan Ban;Haoran Qiao;Zhaolin Yuan;Hong-Ning Dai;Chao Yao;Yu Guo;Mohammad S. Obaidat;George Q. Huang","doi":"10.1109/JAS.2025.125117","DOIUrl":"https://doi.org/10.1109/JAS.2025.125117","url":null,"abstract":"In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network (MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with 75% middle localization F1 score.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 3","pages":"528-538"},"PeriodicalIF":15.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553225","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

A Diffusion Model for Traffic Data Imputation 交通数据输入的扩散模型

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-04 DOI: 10.1109/JAS.2024.124611

Bo Lu;Qinghai Miao;Yahui Liu;Tariku Sinshaw Tamir;Hongxia Zhao;Xiqiao Zhang;Yisheng Lv;Fei-Yue Wang

{"title":"A Diffusion Model for Traffic Data Imputation","authors":"Bo Lu;Qinghai Miao;Yahui Liu;Tariku Sinshaw Tamir;Hongxia Zhao;Xiqiao Zhang;Yisheng Lv;Fei-Yue Wang","doi":"10.1109/JAS.2024.124611","DOIUrl":"https://doi.org/10.1109/JAS.2024.124611","url":null,"abstract":"Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems (ITS) in the real world. As a state-of-the-art generative model, the diffusion model has proven highly successful in image generation, speech generation, time series modelling etc. and now opens a new avenue for traffic data imputation. In this paper, we propose a conditional diffusion model, called the implicit-explicit diffusion model, for traffic data imputation. This model exploits both the implicit and explicit feature of the data simultaneously. More specifically, we design two types of feature extraction modules, one to capture the implicit dependencies hidden in the raw data at multiple time scales and the other to obtain the long-term temporal dependencies of the time series. This approach not only inherits the advantages of the diffusion model for estimating missing data, but also takes into account the multi-scale correlation inherent in traffic data. To illustrate the performance of the model, extensive experiments are conducted on three real-world time series datasets using different missing rates. The experimental results demonstrate that the model improves imputation accuracy and generalization capability.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 3","pages":"606-617"},"PeriodicalIF":15.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553224","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