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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Xiao, Jing Wang, She Cai, Zhen School of Information Engineering Wuhan City Polytechnic University Wuhan430064 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9781665464543

This study delves into the critical role of attitude control in downhole directional drilling tools, focusing on the complex coupling between inclination and azimuth in the motion model, particularly the time-varying nature of azimuth adjustments. By implementing separate control strategies for inclination and azimuth, the research integrates a comprehensive hybrid control system. It rigorously examines the stability of the closed-loop systems and validates the effectiveness and applicability of the hybrid control method through extensive simulations. The system demonstrates significant robustness and adaptability, enhancing drilling precision and efficiency. © 2024 IEEE.

关键词： State feedback

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Robot-Based Auto-labeling System for 6D Pose Estimation 8th

Robot-Based Auto-labeling System for 6D Pose Estimation

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8th International Congress on Information and Communication Technology, ICICT 2023

作者： Lin, Hsien-I. Chang, Jun-Shiang Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Institute of Automation Technology National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9789819930425

6D object pose estimation is an ongoing research area in the field of computer vision. Many existing methods rely on supervised deep learning models which require multiple accurate 6D pose annotations to predict object poses. However, labeling the 6D pose is complex and time-consuming in traditional methods. In this study, we propose a robotic-arm-based 6D object pose auto-labeling approach which has limited human interaction involved. Translations and rotations of the object in the camera coordinate system can be calculated using a sequence of known robot poses and the transformation between the camera and the robot. We also implemented our custom dataset generated by the auto-labeling system in the existing 6D object pose estimation approach. Evaluation results show that the model can recognize our own test dataset and attempted 90% accuracy using ADD metric with 0.05 threshold. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Robotic arms

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Predefined time backstepping control of photovoltaic grid connected inverter 6

Predefined time backstepping control of photovoltaic grid co...

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2023 6th International Conference on Power Electronics and control engineering, ICPECE 2023

作者： Xu, Zhao Ji, Yuehui Chen, Jiaqi Liu, Junjie The School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Industry Systems Tianjin300384 China

The large-scale grid connection of photovoltaic (PV) systems creates great hazards to the operation of power equipment and has a great impact on the stability and reliability of power systems. To achieve stable control and flexible management of PV grid connection, a predefined time adaptive backstepping control method based on the predefined boundary is proposed. Based on the predefined boundary time-varying function, the user's predefined boundary design of the control signal is accomplished to ensure the boundedness of the global signal, which is independent of the initial state of the system. The controller with predefined boundaries is designed based on backstepping control, and the estimation and compensation of perturbations are attained based on adaptive control. The global predefined time stability of the predefined boundary of the closed-loop system is certified using the Lyapunov function. Simulation studies attest to the performance of the predefined time control strategy. © Published under licence by IOP Publishing Ltd.

关键词： Lyapunov functions

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Optimization of Wide-Baseline Stereo Matching Based on Multi-view Geometry

Optimization of Wide-Baseline Stereo Matching Based on Multi...

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2024 China automation Congress, CAC 2024

作者： Xu, Yinhui Shan, Shuo Han, Gongben Fang, Shixiong Zhang, Kanjian Wei, Haikun Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China Shenzhen Research Institute Southeast University Shenzhen China

ISBN: (纸本)9798350368604

Stereo vision plays a crucial role in scientific expeditions and facility maintenance. However, fixed-baseline stereo vision lacks accuracy for long-distance measurements, while wide-baseline stereo vision encounters occlusion issues at short distances. In this study, a wide-baseline stereo matching based on multi-view geometric constraints is proposed. Initially, the camera poses of multiple wide-baseline images are estimated, followed by image rectification and depth estimation. Subsequently, the disparity searching is constrained using geometric relationships among the views, resulting in more precise depth maps. Experiments were conducted to verify the superiority of the proposed method. The results indicate that the proposed method achieves an RMSE as low as 0.15 meters, even with invalid depth points. Compared to traditional stereo vision methods, accuracy is improved by approximately 35%, and robustness is significantly enhanced. In the aircraft runway scenario, overall depth map accuracy is higher, and occluded areas are significantly reduced. © 2024 IEEE.

关键词： Stereo vision

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Infrared Thermal Image Fault Detection of Electric Motor Based on Improved VGG16 Network Model 6

Infrared Thermal Image Fault Detection of Electric Motor Bas...

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6th International Conference on Communications, Information System and Computer engineering, CISCE 2024

作者： Zhu, Xianghua Hu, Shan Bing, Zhigang Zhao, Di School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Key Laboratory of Information Sensing & Intelligent Control Tianjin China Engineering Teaching Practice Training Center of Tiangong University Tianjin China

ISBN: (纸本)9798350353174

As a core component of modern industry, electric motors are widely used in important fields such as electric power, machinery and national defense, and the fault detection of their thermal images faces problems such as diverse fault types, insufficient complex data processing capability and long training time. To address the above problems, this paper proposes a method for fault detection of infrared thermal images of electric motors based on an improved VGG16 network model. In the model construction and implementation, based on the VGG16 network model, the significant optimization of training time and accuracy is achieved by improving the structure of the latter layers of the model and introducing the migration learning strategy, as well as adding the callback function, the AdamW optimizer and the focal point loss function to the model. The experimental results show that the improved VGG16 model increases the average accuracy by 12.96%, reduces the average loss rate by about 23 times, and shortens the training time by half in infrared thermal image fault detection of induction motors. In the model performance evaluation, whether adjusting the test conditions or conventional model evaluation methods, the results reflect the superiority of the improved model in the realm of infrared thermal image anomaly identification of induction motors, which has practical application value. © 2024 IEEE.

关键词： Electric motors

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Disagreement and Antagonism in Signed Networks: A Survey

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1166-1187页

作者： Yuxin Wu Deyuan Meng Zheng-Guang Wu Seventh Research Division Beihang University(BUAA)and also with the School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100191China National Laboratory of Industrial Control Techno-logy Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China IEEE

Signed networks refer to a class of network systems including not only cooperative but also antagonistic interactions among *** to the existence of antagonistic interactions in signed networks,the agreement of nodes may not be established,instead of which disagreement behaviors generally *** paper reviews several different disagreement behaviors in signed networks under the single-integrator linear dynamics,where two classes of topologies,namely,the static topology and the dynamic topology,are *** the static signed networks with the adjacency weights as(time-varying)scalars,we investigate the convergence behaviors and the fluctuation behaviors with respect to fixed topologies and switching topologies,respectively,and give some brief introductions on the disagreement behaviors of general time-varying signed ***,several classes of behavior analysis approaches are also *** the dynamic signed networks with the adjacency weights as transfer functions or linear time-invariant systems,we show the specific descriptions and characteristics of them such that the disagreement behaviors can be obtained by resorting to the derived static signed ***,we give their applications to the behavior analysis of static signed networks in the presence of high-order dynamics or communication delays.

关键词： Antagonistic interaction disagreement behavior dynamic topology signed network static topology

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A Defect Detection Algorithm of Round Tablets Based on Image Information 9

A Defect Detection Algorithm of Round Tablets Based on Image...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Zhang, Lianqi Zhou, Rui Sun, Yuan Chen, Xiaojin Yang, Zhiwang College of Electrical Engineering and Automation Xiamen University of Technology Fujian Xiamen China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Fujian Xiamen China

ISBN: (纸本)9798350376548

This paper presents a novel circular tablet defect detection algorithm based on machine learning techniques to address the challenge of insufficient data for training samples. Utilizing cameras, lenses, and light sources, we establish an image acquisition hardware system for capturing tablet images, and on the basis of image preprocessing, the designed defect detection algorithm is used for detection, forming a complete and efficient round tablet defect detection process. The experimental results have been demonstrated that the performance of the sample missed detection rate was 0.2%, the false detection rate is 0.6%, and the total error rate is 0.8%, all lower than 1%. The proposed detection algorithm does not require sample training and can be well applied to the identification of defects such as abnormal tablet circular areas and foreign matter on the surface of tablets. © 2024 IEEE.

关键词： Detection algorithm Image information Tablet defects

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Fault Diagnosis Method for On-Board Interface Equipment of CTCS-3 Based on Temporal Knowledge Graph Completion 21

Fault Diagnosis Method for On-Board Interface Equipment of C...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Zhou, Bingyan Zhang, Daqian Lv, Jidong Liu, Hongjie Zhao, Zixu Luo, Zhengwei School of Automation and Intelligence Beijing Jiaotong University Beijing China Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation and Control System Beijing China

ISBN: (纸本)9798350365221

Chinese Train control System level 3 (CTCS-3) train control onboard equipment plays a crucial role in ensuring train safety and improving operational efficiency. And the on-board interface equipment enables the interaction between the on-board Automatic Train Protection (ATP), ground equipment, drivers, and trains. While its fault accounts for a relatively high proportion of faults, therefore, this paper proposed a fault diagnosis method for on-board interface equipment based on temporal knowledge graph completion. Firstly, this method introduces temporal series to integrate travel logs and fault statistics, which extract fault phenomena and perform entity alignment, construct the temporal knowledge graph. Secondly, on this basis, we constructed a fault diagnosis network based on knowledge graph completion, which incorporates the Temporal-Translating Embedding (T - TransE) vectorization algorithm, Bidirectional Long Short-Term Memory (Bi-LSTM), and Self-Attention (SA) mechanism for temporal feature extraction. Finally, the T - TransE vectorization model was pretrained using the on-board interface equipment fault data from a railroad station in recent years for selecting the most effective temporal integration method. In order to validate the superiority of the proposed fault diagnosis method and the effectiveness of the data combination method, the diagnostic network without data combination and temporal relationship introduction, and other common fault diagnostic networks, were tested using the on -board fault data. Compared with the following fault diagnosis methods, the model proposed in this paper achieved the highest fault diagnostic accuracy of 96.8%. © 2024 IEEE.

关键词： Knowledge graph

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Distributed Cooperative Learning for Discrete-Time Strict-Feedback Multi Agent Systems Over Directed Graphs

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1831-1844页

作者： Min Wang Haotian Shi Cong Wang IEEE the School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641 Peng Cheng Laboratory Shenzhen 518055China the School of Control Science and Engineering Shandong UniversityJinan 250061China the Center for Intelligent Medical Engineering Shandong UniversityJinan 250061China

This paper focuses on the distributed cooperative learning(DCL)problem for a class of discrete-time strict-feedback multi-agent systems under directed *** with the previous DCL works based on undirected graphs,two main challenges lie in that the Laplacian matrix of directed graphs is nonsymmetric,and the derived weight error systems exist n-step *** novel lemmas are developed in this paper to show the exponential convergence for two kinds of linear time-varying(LTV)systems with different phenomena including the nonsymmetric Laplacian matrix and time ***,an adaptive neural network(NN)control scheme is proposed by establishing a directed communication graph along with n-step delays weight updating ***,by using two novel lemmas on the extended exponential convergence of LTV systems,estimated NN weights of all agents are verified to exponentially converge to small neighbourhoods of their common optimal values if directed communication graphs are strongly connected and *** stored NN weights are reused to structure learning controllers for the improved control performance of similar control tasks by the“mod”function and proper time series.A simulation comparison is shown to demonstrate the validity of the proposed DCL method.

关键词： Cooperative learning control directed graphs discrete-time nonlinear system neural networks(NNs) strict-feedback systems

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Integrated Prediction of Unfavorable Geology in Main Tunnel Considering the Geological Conditions of Parallel Tunnel

Integrated Prediction of Unfavorable Geology in Main Tunnel ...

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2024 China automation Congress, CAC 2024

作者： Zhang, Meng Gan, Chao Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

Currently, the advanced geological prediction for the main tunnel from the parallel tunnel often employs parallel deduction of detection conclusions, which faces issues such as a lack of diverse geological exploration information, a lack of analysis of geological structures and poor accuracy. In this paper, an integrated prediction method for unfavorable geology in main tunnel considering the geological conditions of parallel tunnel is proposed, which consists of three stages. In the first stage, based on the forecast mileage range and tunnel excavation conditions, the process is divided into four specific cases. In the second stage, it deduces the geology of the main tunnel along the orientation of rock strata occurrence or joint to parallel tunnel and selects the results of the rock strata occurrence or joint deduction according to the distance of the deduction. In the last stage, it deduces the geological conditions of parallel tunnel face and the integration of geophysical and drilling information for predictive conclusions based on the four specific cases. The proposed method offers higher prediction accuracy for rock mass integrity and surrounding rock grades compared to parallel deduction method. © 2024 IEEE.

关键词： Miocene

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