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63rd IEEE Conference on Decision and control, CDC 2024

作者： Duan, Mengmeng Zhu, Shanying Yang, Ziwen Chen, Cailian Guan, Xinping The authors are with the Department of Automation Shanghai Jiao Tong University Shanghai 200240 ChinaKey Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China and also Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (纸本)9798350316339

In this paper, we investigate the distributed optimization problem for heterogeneous linear multi-agent systems with unknown disturbances. By applying the primal-dual method and the time-scale separation technique, a distributed dynamic controller without using any disturbance information is proposed. Based on the optimal condition, the relationship between the optimal solution and the equilibrium point of the system is established, and it is shown that the distributed optimization problem is solved provided that the closed-loop system is stable. Then, inspired by the nonsingular perturbation analysis, it is proved that the closed-loop system is exponentially input-to-state stable with respect to the derivative of the disturbance. Numerical examples are provided to illustrate the theoretical results. © 2024 IEEE.

关键词： Closed loop systems

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Health monitoring by optical fiber sensing technology for rechargeable batteries

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eScience 2024年第1期4卷 79-95页

作者： Yi Zhang Yanpeng Li Zezhou Guo Jianbo Li Xiaoyu Ge Qizhen Sun Zhijun Yan Zhen Li Yunhui Huang State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access SystemWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhanHubei430074China Henan Key Laboratory of Laser and Opto-electric Information Technology School of Electrical and Information EngineeringZhengzhou UniversityZhengzhouHenan45001China

With the proposal of a“smart battery,”real-time sensing by rechargeable batteries has become progressively more important in both fundamental research and practical ***,many traditional sensing technologies suffer from low sensitivity,large size,and electromagnetic interference problems,rendering them unusable in the harsh and complicated electrochemical environments of *** optical sensor is an alternative approach to realize multiple-parameter,multiple-point measurements ***,it has garnered significant *** analyzing these measured parameters,the state of interest can be decoded to monitor a battery's *** review summarizes current progress in optical sensing techniques for batteries with respect to various sensing parameters,discussing the current limitations of optical fiber sensors as well as directions for their future development.

关键词： Optical fiber sensing Rechargeable battery Real-time sensing Health monitoring

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Cross-Modality Guided Multi-Scale Feature Representation Based Image Compression for Industrial Scene Understanding 22

Cross-Modality Guided Multi-Scale Feature Representation Bas...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Tu, Jingzheng Yan, Yan Lu, Ying Chen, Cailian Zhou, Shiru China Academy of Aerospace Science and Innovation Beijing100088 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9798331527471

Industrial surveillance videos capture subsequent video frames and deliver them to processing servers for video analytics. In such a case, image compression is a promising technology in industrial scene understanding due to its reduced transmission burden. Existing works focus on establishing macroscopic visual feature maps that contain compact image information. In this article, a cross-modality guided multi-scale feature representation based image compression method is proposed for understanding industrial scenes. Firstly, an image compressing framework with multi-grained representation (MGRIC) is proposed for industrial scene understanding, which builds image patch, structure, semantic, and signal levels feature maps. Secondly, an encoder-decoder architecture is designed for image compression with diverse granularities. Thirdly, an interaction policy between different levels is developed to ensure the subsequent level’s decoding. Experiments on the CUB-200-2011 dataset demonstrate that the proposed MGRIC method achieves competitive performance, which verifies its effectiveness. © 2024 IEEE.

关键词： Decoding

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Optimal control Synthesis of Markov Decision Processes for Efficiency with Surveillance Tasks 63

Optimal Control Synthesis of Markov Decision Processes for E...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Chen, Yu Yin, Xuanyuan Ye, Hao Li, Shaoyuan Yin, Xiang Shanghai Jiao Tong University Department of Automation and Key Laboratory of System Control and Information Processing Shanghai200240 China Nanyang Technological University School of Chemistry Chemical Engineering and Biotechnology Singapore Tsinghua University Department of Automation China

ISBN: (纸本)9798350316339

We investigate the problem of optimal control synthesis for Markov Decision Processes (MDPs), addressing both qualitative and quantitative objectives. Specifically, we require the system to fulfill a qualitative surveillance task in the sense that a specific region of interest can be visited infinitely often with probability one. Furthermore, to quantify the performance of the system, we consider the concept of efficiency, which is defined as the ratio between rewards and costs. This measure is more general than the standard long-run average reward metric as it aims to maximize the reward obtained per unit cost. Our objective is to synthesize a control policy that ensures the surveillance task while maximizes the efficiency. We provide an effective approach to synthesize a stationary control policy achieving -optimality by integrating state classifications of MDPs and perturbation analysis in a novel manner. Our results generalize existing works on efficiency-optimal control synthesis for MDP by incorporating qualitative surveillance tasks. © 2024 IEEE.

关键词： Markov processes

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Diagnosis of Occupational Pneumoconiosis Based on Adaptive Feature Fusion and Multi-class Loss Function

Diagnosis of Occupational Pneumoconiosis Based on Adaptive F...

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2024 China Automation Congress, CAC 2024

作者： Zhao, Qian Guo, Yinan Gong, Dunwei China University of Mining and Technology Xuzhou China China University of Mining and Technology Beijing China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Qingdao University of Science and Technology Qingdao China

ISBN: (纸本)9798350368604

Pneumoconiosis, as the most prevalent and severe occupational disease in China, is categorized into four stages based on the area of small shadows in lungs. Previous diagnostic methods have limited accuracy for identifying different stages due to complex and diverse lesions of pneumoconiosis, as well as the difficulty of collecting rich X-ray images of patients. To address the issues, a novel diagnostic method based on adaptive feature fusion and multi-class loss function is proposed. First, the prototype network is introduced to establish a diagnostic model under the insufficient images, with the purpose of distinguishing the disease stage by the distance between the features of various samples. Following that, the multi-channel and multi-level feature fusion modules are proposed, respectively. These modules incorporate a gate-based adaptive selection mechanism to efficiently integrate the most important features from different channels and levels. Finally, the multi-class loss function is designed to train the diagnostic model of pneumoconiosis. The experimental results on a self-built dataset of chest X-ray radiographs demonstrate that the proposed method outperforms ten comparative methods in terms of comprehensive performance. © 2024 IEEE.

关键词： X ray radiography

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ACBL:Attentive CNN-BiLSTM Model For Trajectory Prediction 43

ACBL:Attentive CNN-BiLSTM Model For Trajectory Prediction

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43rd Chinese control Conference, CCC 2024

作者： Yang, Gan Wang, Guangwei Li, Yichen Yu, Wenbin Shanghai Jiao Tong University Department of Automation Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Tianjin Navigation Instruments Research Institute Tianjin300131 China

ISBN: (纸本)9789887581581

Predicting the future trajectory of a target becomes particularly challenging while dealing with occlusion conditions, where current information is unavailable, and historical data becomes the only basis for prediction. In this paper, we propose a trajectory prediction model that utilizes scaled dot product attention mechanism, a convolution neural network, and a bidirectional long short term memory network. The scaled dot product attention mechanism gauges the impact of historical sequences, while the convolution neural network extracts intricate feature information from these sequences. Subsequently, these data is fed into the bidirectional long short term memory network to forecast the target's navigation path. Experimental results highlight that the Attentive CNN-BiLSTM (ACBL) network which we proposed has lower root mean square error (RMSE) by 23 % on average than current methods. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Convolutional neural networks

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Decomposing Visual and Semantic Correlations for Both Fully Supervised and Few-Shot Image Classification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1658-1668页

作者： Zhang, Chunjie Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Most image classification methods are designed to either boost the classification accuracies with abundant supervision, or cope with the shortage of supervision information. This is often achieved by using the visual and semantic information of other sources. However, these methods use the visual and semantic information within the same class independently, leaving their intrinsic correlations unconsidered. Objects and disturbing components as well as noise exist on the same image. Besides, semantic representations also contain noisy information. To solve the problems mentioned above, we propose a novel method for both fully supervised image classification and few-shot image classification by decomposing visual and semantic correlations. We jointly explore the intrinsic correlations of visual and semantic information of images within the same class. For each class, we decompose its visual and semantic correlations using low-rank and sparse constraint respectively. The decomposed low-rank parts character the intrinsic correlations of images can be used in a linear transformation way. Using the decomposed parts of each class, Classification can be achieved by reconstruction error minimization. We conduct experiments on several datasets for both fully supervised image classification and few-shot image classification. Experimental results well show the effectiveness of the proposed method. © 2020 IEEE.

关键词： Semantics

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Analysis of the Impact of COVID-19 Infection Rate on the Selection of Nucleic Acid Testing Options 29th

Analysis of the Impact of COVID-19 Infection Rate on the Sel...

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29th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2023

作者： Ma, Mimi Wang, Demin Zuo, Zhibin Deng, Miaolei Henan University of Technology Zhengzhou450001 China Key Laboratory of Grain Information Processing and Control Ministry of Education Henan University of Technology Zhengzhou China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Zhengzhou China

ISBN: (纸本)9783031449468

Novel mixed coronavirus nucleic acid tests can reduce testing time and cost, improve the efficiency of nucleic acid testing, and ensure that the required population nucleic acid tests are completed in a short period of time. In this paper, we analyze the number of tests for various mixed testing protocols at different positive rates by using a mathematical testing model to derive the most suitable mixed nucleic acid testing protocols at different positive rates. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Coronavirus

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Policy iteration-based adaptive optimal control for Markov jump systems: a transition-probability-free asynchronous approach

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Science China(information Sciences) 2024年第11期67卷 363-364页

作者： Weidi CHENG Chengcheng REN Shuping HE Changyin SUN Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province Engineering Research Center of Autonomous Unmanned System Technology (Ministry of Education) School of Artificial Intelligence Anhui University

The controller and filter design problems of Markov jump systems(MJSs) have gained significant attention over the past few decades. These studies include various aspects,including stochastic stabilization [1], optimal tracking control [2], and dissipative filter design [3]. Although numerous publications address the optimal controller design for MJSs, the issue of hidden MJSs, particularly those with mismatched jumping modes between the system and the controller, has rarely been explored.

关键词： Markov processes

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Transmission line inspection system based on high performance unmanned helicopters 4

Transmission line inspection system based on high performanc...

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4th International Conference on Mechanical, Electronics, and Electrical and Automation control, METMS 2024

作者： Li, Wei Li, Ming Meng, Xiangjiao Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing Tianjin Zhong Wei Aerospace Data System Technology Co. Ltd. Tianjin China

ISBN: (数字)9781510679887

ISBN: (纸本)9781510679870

A high-performance unmanned helicopter based transmission line inspection system is proposed to address the issues of low single operation efficiency, low degree of autonomy, and single operation mode in the current multi rotor unmanned aerial vehicle inspection system. This system is based on an unmanned helicopter platform, with customized research and development of load quick replacement and mounting structural components, airborne load control units, optoelectronic pods, autonomous inspection software systems, and other parts. The number of towers that can be inspected in a single fine inspection operation is not less than 20 (visibility, distance between towers is 0.3 km), and the photographic data can meet the requirements of identifying pin level targets (10mm) 50 meters away. Through flight verification testing, it has been shown that the various working modes of the system are operating normally, and autonomous inspections do not require human intervention, greatly improving the efficiency of transmission line inspections. © 2024 SPIE.

关键词： Electric lines

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