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第42届中国控制会议

作者： Zaishan Zhang Wenwu Zhu Ke Yu Xiangyu Wang Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Electrical Engineering and Automation Hefei University of Technology

In this paper,a nonsmooth observer considering friction compensation is proposed for the sensorless permanent magnet synchronous motor(PMSM) to estimate the rotor position and *** is one of the main factors affecting the tracking accuracy of the motor at low speed,especially in the back and forth motion of the ***,based on the Stribeck friction model,a nonlinear friction model of the motor is ***,a nonsmooth observer with friction compensation is designed to estimate the position and speed of the rotor,and the lumped disturbance of the system at the same ***,the stability analysis of this nonsmooth observer is ***,the effectiveness of the proposed method is verified by the simulation results.

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Multi-scale discriminative regions attention network for fine-grained vehicle classification

Journal of Network Intelligence

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Journal of Network Intelligence 2021年第2期6卷 164-177页

作者： Rong, Wen-Zhong Han, Jin Cai, Ying-Hao Liu, Gen College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Fine-grained vehicle classification is a challenging task in computer vision due to the low intra-class variance. Some methods have been developed to improve the accuracy of fine-grained vehicle classification by improving the ability of discriminative features extraction, but there is still room for further improvement in the localization accuracy of vehicle discriminative regions. Based on deep convolutional neural networks, we focus on finding a more efficient structure that pays more attention to the discriminative image regions to enhance the ability of fine-grained vehicle classification. We propose a novel Multi-Scale Discriminative Regions Attention Network (MS-DRAN), which extracts feature maps through ResNet-50 backbone network and generates multi-scale feature maps by a Feature Pyramid Network (FPN). Then, MS-DRAN generates discriminative regions attention maps on the multi-scale feature maps. The attention maps from shallow layer perform pixel-level multiplication with the feature maps from deeper layer. By this way, the network gradually extracts a more discriminating feature maps for classification. We also design a multi-task loss function to associate the classification results for each scale and optimize the network parameter in training. Lastly, we validate the MS-DRAN on Stanford Cars-196 dataset and CompCars dataset and achieves 94.3% and 98.1% in accuracy, respectively. ©2021 ISSN 2414-8105 (Online).

关键词： Classification (of information)

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MRO Configuration Management for complex Products

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Journal of systems Science and systems engineering 2022年第3期31卷 359-380页

作者： Chunliu Zhou Lian Qi Xiaobing Liu Hongguang Bo Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMaanshan 243002China School of Management Science and Engineering Anhui University of TechnologyMaanshan 243032China Rutgers Business School RutgersThe State University of New JerseyPiscatawayNJ 08854United State School of Economics and Management Dalian University of TechnologyDalian 116023China

Configuration management(CM)is an effective method for data modeling and change management in product development,but the study of how it can be adapted for complex product maintenance,repair and overhaul(MRO)has thus far been *** propositions are put forward on the basis of a literature review and verified by a case of a high-speed train MRO *** findings show that CM can be used in MRO data management with adjustments in its ***,MRO-CM planning considers both multistage service and single-stage service to keep data consistent and ***,MRO data integration with the design/production phase should be considered during configuration ***,baselines and change rules are developed for change ***,status accounting and auditing can be repeatedly used in MRO data management.A systematic MRO-CM framework is generated to assist MRO practitioners in understanding the relationships among different MRO-CM *** paper contributes to expanding the theory of CM in MRO for complex products and provides an effective method for managing MRO data from systematic engineering insights.

关键词： Configuration management MRO Service data management case study

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Single-Domain Generalization Combining Geometric Context Toward Instance Segmentation of Track Components

Single-Domain Generalization Combining Geometric Context Tow...

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International Joint Conference on Neural Networks (IJCNN)

作者： Shixiang Su Songlin Du Dezhou Wang Shuzhen Tong Xiaobo Lu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China School of Instrument Science and Engineering Southeast University Nanjing China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

A stable track components segmentation model should have consistent performance across a broad spectrum of railroad conditions, particularly in unfamiliar locations. Despite this, satisfying this requirement proves challenging when working with a limited track dataset, as there is a substantial domain shift between the given dataset and unobserved distributions. The goal of this paper is to improve the generalization ability of track component segmentation in situations where single-domain training data is available. Toward this end, a novel track component instance segmentation method combining the geometric context is proposed. First, we design an initial mask prediction head (IMPH) that utilizes predicted box output from the object detector to generate initial masks by merging the geometric priors of track components. Meanwhile, a multiscale feature fusion structure is introduced to encourage IMPH to better capture the geometric context. Then, a final mask refinement head (FMRH) is introduced to get higher quality masks with a geometry-gated aggregation strategy. On the basis of experiments on track datasets, it was determined that the heads can be incorporated with several types of detection frameworks and have demonstrated consistent generalization enhancements across multiple object detectors. Furthermore, our method substantially enhances segmentation performance on various unobserved domains.

关键词： Instance segmentation Geometry Accuracy Neural networks Merging Training data Detectors

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Real-time In-situ Defect Detection in 3D Printing of Continuous Fiber-Reinforced Composites 4

Real-time In-situ Defect Detection in 3D Printing of Continu...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Yue, Zhijian Shen, Zhen Dong, Xiangyang Fang, Qihang Wang, Weixing Dong, Xisong Xiong, Gang Wang, Fei-Yue University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing100190 China Qingdao Academy of Intelligent Industries Intelligent Manufacturing Center Qingdao266109 China Chinese Academy of Sciences Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China Chinese Academy of Sciences State Key Laboratory for Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350349252

With the development of continuous fiber-reinforced composites (CFRCs) 3D printing technology, timely, efficient and accurate detection of fiber path defects is essential for ensuring product quality and performance. However, challenges still need to be addressed in this field, such as inadequate training data coverage and the complexity of fiber path structures. These factors hinder the capability of traditional methods to accurately assess the status of printed products. Therefore, developing accurate and robust fiber path defect detection techniques is crucial for CFRCs 3D printing technology. In this paper, we propose a precise detection method for fiber path defects in CFRCs 3D printing using the YOLOv7 object detection model combined with a Squeeze-and-Excitation (SE) attention mechanism. By introducing the SE attention mechanism, we enhance the perception capability of the YOLOv7 model for crucial features, thereby improving the accuracy of fiber path defect detection. The experimental results show that the YOLOv7 model, when augmented with an attention mechanism, achieves an average accuracy of 93.9% in identifying fiber path defects during the printing process. Compared to models without this attention mechanism, the results show that there is 10.7% increase, with a notably enhanced learning capacity during the training phase, which substantiates the efficacy and practicality of the proposed approach. © 2024 IEEE.

关键词： Fiber reinforced plastics

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Sequential fusion estimation for multisensor systems with non-Gaussian noises

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Science China(Information Sciences) 2020年第12期63卷 153-165页

作者： Liping YAN Chenying DI Q.M.Jonathan WU Yuanqing XIA Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Department of Electrical and Computer Engineering University of Windsor

The sequential fusion estimation for multisensor systems disturbed by non-Gaussian but heavytailed noises is studied in this paper. Based on multivariate t-distribution and the approximate t-filter,the sequential fusion algorithm is presented. The performance of the proposed algorithm is analyzed and compared with the t-filter-based centralized batch fusion and the Gaussian Kalman filter-based optimal centralized fusion. Theoretical analysis and exhaustive experimental analysis show that the proposed algorithm is effective. As the generalization of the classical Gaussian Kalman filter-based optimal sequential fusion algorithm, the presented algorithm is shown to be superior to the Gaussian Kalman filter-based optimal centralized batch fusion and the optimal sequential fusion in estimation of dynamic systems with non-Gaussian noises.

关键词： state estimation sequential fusion non-Gaussian disturbance heavy-tailed noise multivariate $t$-distribution

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Robust control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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2024 China Automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

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Smoky Vehicle Detection Based on Improved Vision Transformer 21

Smoky Vehicle Detection Based on Improved Vision Transformer

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5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Yuan, Li Tong, Shuzhen Lu, Xiaobo School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781450389853

The harmful exhaust emissions of fuel vehicles in theworld are damaging to human health and the environment, thus detecting smoky vehicles from real road environment is significant. At present, methods of smoky vehicle detection based on deep learning have the problem of high false-positive rate. To improve the performance, a two-stage video smoky vehicle detection algorithm based on the smoke classification in the core region from detected vehicle object boxes is proposed in this paper. Specifically, the vehicle object detection is realized by the algorithm based on YOLOv3. The smoke classification is realized by combining Vision Transformer and distillation, and the loss function is optimized in the training process. Experimental results on our smoky vehicle dataset have shown that the improved model achieves an F1 score over 0.4, precision over 0.4, recall nearly 0.1 improvement compared with the basic model, which can effectively reduce the false-positive rate during detection.. © 2021 Association for Computing Machinery. All rights reserved.

关键词： Smoke

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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Exploring the Economic Feasibility of Advanced Air Mobility in the Early Stages

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 4826-4830页

作者： Jingqiu Guo Long Chen Lingxi Li Xiaoxiang Na Ljubo Vlacic Fei-Yue Wang Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University–Purdue University Indianapolis (IUPUI) Indianapolis IN USA Department of Engineering University of Cambridge Cambridge U.K. Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith University Nathan QLD Australia State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.

关键词： Active appearance model Costs Economics Transportation Helicopters Aircraft propulsion Public transportation

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