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A Framework of LSTM Neural Network Model in Multi-Time Scale Real-Time Prediction of Ship Motions in Head Waves

船舶力学 2024年第12期28卷 1803-1819页

作者： CHEN Zhan-yang ZHAN Zheng-yong CHANG Shao-ping XU Shao-feng LIU Xing-yun Department of Ocean Engineering Harbin Institute of Technology at WeihaiWeihai 264209China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China Flight Control System Department AVIC Xi'an Flight Automatic Control Research InstituteXi'an 710065China

Ship motions induced by waves have a significant impact on the efficiency and safety of offshore ***-time prediction of ship motions in the next few seconds plays a crucial role in performing sensitive ***,the obvious memory effect of ship motion time series brings certain difficulty to rapid and accurate ***,a real-time framework based on the Long-Short Term Memory(LSTM)neural network model is proposed to predict ship motions in regular and irregular head waves.A 15000 TEU container ship model is employed to illustrate the proposed *** numerical implementation and the real-time ship motion prediction in irregular head waves corresponding to the different time scales are carried out based on the container ship *** related experimental data were employed to verify the numerical simulation *** results show that the proposed method is more robust than the classical extreme short-term prediction method based on potential flow theory in the prediction of nonlinear ship motions.

关键词： deep learning LSTM ship motion real-time prediction irregular waves

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HCRI: A ROS2 Human Collision Object Interface for Robotic Manipulation Planning

HCRI: A ROS2 Human Collision Object Interface for Robotic Ma...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Wang, Changcong Wei, Chongyi Bai, Shaoping Li, Yibin Tian, Xincheng Zhou, Lelai Shandong University The Center for Robotics School of Control Science and Engineering Jinan250061 China The Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan250061 China Aalborg University Department of Materials and Production Aalborg9220 Denmark

ISBN: (纸本)9798350327182

Human-Robot Collaboration (HRC) is people and robots work together in the same workspace to achieve shared goals. To ensure safety, robots need to perceive the position of the human body for planning purposes. However, there is no universal method for converting the human body into collision objects. To solve this problem, we propose an interface to convert the human body segments into collision objects in the robot planning scene. The interface estimates the human body Skinned Multi-Person Linear model (SMPL) by RGB image and measures the collision object size of the corresponding body segment. The corresponding size of collision objects are added to the corresponding positions of the human pose estimated by different types of sensors. The accuracy of human size estimation is verified on TotalMocap of AMASS. The interface with OctoMap is compared to evaluate the efficiency and the validity on interface is verified on the robot UR5e. © 2023 IEEE.

关键词： Image segmentation

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Data-driven Fault Diagnosis Method Based on Fusion of Multi-direction and Multi-source Signals 5

Data-driven Fault Diagnosis Method Based on Fusion of Multi-...

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5th International Conference on Intelligent Autonomous systems, ICoIAS 2022

作者： Yang, Yang Wang, Junda Li, Ning Shanghai Jiaotong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

As a pivotal mechanical component of turbine drive-chain, gearbox suffers from various accidents and fault diagnosis could remarkably enhance its reliability and maintain running safety and lifetime. Vibration-based analysis on single-channel is mainly adopted in previous diagnostic, which cannot catch full vibration inner information in gearbox sensors and bring model performance down. In this paper, a novel method based on the fusion of multi-direction and multi-source signals and the convolutional neural network (MDMS-CNN) is presented. This method can obtain multi-dimensional feature maps from MDMS and preserve the time correlation among different signal sequences. First, features from MDMS are extracted via a corrosion conversion method that converts signals into two-dimensional (2-D) gray images. Then, homologous images are spliced into same channels, while heterogeneous images are superimposed to different channels. Finally, fusion features are input into CNN for fault classification. In experiments, the method is validated on a gearbox diagnosis case. Results have shown that the proposed method achieves 99.86% recognition accuracy and faster convergence speed compared to others. © 2022 IEEE.

关键词： Failure analysis

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Global Update Guided Federated Learning 41

Global Update Guided Federated Learning

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第41届中国控制会议

作者： Qilong Wu Lin Liu Shibei Xue Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Electronic Information Engineering Shanghai Dianji University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Federated learning protects data privacy and security by exchanging models instead of ***,unbalanced data distributions among participating clients compromise the accuracy and convergence speed of federated learning *** alleviate this problem,unlike previous studies that limit the distance of updates for local models,we propose global-updateguided federated learning(FedGG),which introduces a model-cosine loss into local objective functions,so that local models can fit local data distributions under the guidance of update directions of global ***,considering that the update direction of a global model is informative in the early stage of training,we propose adaptive loss weights based on the update distances of local *** simulations show that,compared with other advanced algorithms,FedGG has a significant improvement on model convergence accuracies and ***,compared with traditional fixed loss weights,adaptive loss weights enable our algorithm to be more stable and easier to implement in practice.

关键词： Federated Learning Cosine Similarity Adaptive Loss Weights

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Analytical Representation of Data-driven Transient Stability Constraint and Its Application in Preventive control

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Journal of Modern Power systems and Clean Energy 2022年第5期10卷 1085-1097页

作者： Yiwei Fu Xiaohua Zhang Lei Chen Zengyao Tian Kaiyuan Hou Haikuan Wang State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijing 100084China State Grid Jibei Electric Power Company Beijing 100053China Northeast China Branch of State Grid Corporation of China Shenyang 110180China

Accurate transient stability assessment(TSA) and effective preventive control are important for the stable operation of power systems. With the superiorities in precision and efficiency, data-driven methods are widely used in TSA nowadays. Data-driven TSA model can be adopted in the stability constraints of preventive control optimization, but existing methods are mostly iteration-based ones, which may result in low efficiency, sometimes even non-convergence. In this paper,an analytical representation method of data-driven transient stability constraint is proposed based on a non-parametric regression model built for TSA. Key feature extraction and dominant sample selection are proposed to reduce the scale of the TSA model, and bi-level linearization is applied to further modify *** preventive control model is then formulated as a mixed-integer linear program(MILP) problem with the linearized analytical data-driven transient stability constraint, which can be solved without iterations. An overall procedure of datadriven TSA and preventive control is finally developed. Case studies show that the proposed method has high accuracy in TSA and can achieve effective preventive control of power system with high efficiency.

关键词： Data-driven critical clearing time transient stability constraint non-parametric regression optimal preventive control

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Multi-party secure communication using blockchain over 5G

Multi-party secure communication using blockchain over 5G

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Archana, K. Kareem, Z.H. Al-Farhani, Liwa H. Bagyalakshmi, K. Jenvi, Ignatia K. Majella Kumar, Ashok Department of Computer Engineering Pimpri Chinchwad College of Engineering and Research Maharashtra Pune India Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq System Analysis Control and Information Processing dep Academy of Engineering RUDN University Moscow Russia Sri Ranganathar Institute of Engineering and Technology Coimbatore India Mathematics Department Saveetha School of Engineering SIMATS Saveetha Nagar Chennai India Department of Computer Science Banasthali Vidyapith Rajasthan Banasthali India

ISBN: (纸本)9781032669663

One of the most critical problems facing the blockchain technology industry right now is how to protect the privacy of users’ data on the blockchain in a way that is both effective and cheap. Based on the Pedersen commitment and the Schnorr protocol, this study comes up with a secure multi-party computing protocol (BPLSM). By making the structure of the protocol and doing formal proof calculations, it has been shown that the protocol can be used in the blockchain network to combine private messages for efficient signing while keeping people’s identities secret. Furthermore, by looking at the nature and security of the protocol, it is also possible to find that the BPLSM protocol on the blockchain has a low cost of computing and a high level of information secrecy. Furthermore, it was found that the BPLSM protocol takes less time to check than the current mainstream BLS signature in a simple multi-party transaction with a fixed number of participants. © 2024 The Author(s).

关键词： Blockchain

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MPPT Algorithms for Wind Turbines: Review and Comparison 29

MPPT Algorithms for Wind Turbines: Review and Comparison

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29th International Workshop on Electric Drives: Advances in Power Electronics for Electric Drives, IWED 2022

作者： Aleksandr, Lukin Demidova, Galina Alassaf, Omar Lukichev, Dmitry Rassolkin, Anton Vaimann, Toomas ITMO University Faculty of Control System and Robotics Saint-Petersburg Russia Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia

ISBN: (纸本)9781665467865

Wind turbines play an important role in energy generation using renewable sources. The wind is very changeable, and such turbines require techniques for finding and tracking maximum power density. The presented work includes an overview of maximum power point tracking techniques applicable to small-size wind turbines based on the Magnus effect. An overview of existing algorithms is presented. Overviewed algorithms are assessed using a simulation in MATLAB with a model of the experimental Magnus effect wind turbine. © 2022 IEEE.

关键词： Wind power

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Inertia Support Strategy for DC Collecting system of Wind Turbine Generator

Inertia Support Strategy for DC Collecting System of Wind Tu...

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Energy Storage and Conversion (ISESC), CPSS & IEEE International Symposium on

作者： Zenyang Liu Kai Sun Huan Wang Junlong Lu Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China Renewable Energy Power Generation System Research Department Institute of Electrical Engineering Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350380514

ISBN: (纸本)9798350380521

In wind turbine generators system, lacking of inertia is a common problem. In AC collecting system, some researches have been done to solve this problem. However, in DC collecting system, few researches were done. This paper analyzes the analogies between AC and DC collecting system and the virtual capacitor control corresponding to the virtual synchronous generator control. Small signal models of different precision are proposed considering the LLC resonant converter used for stepping-up. The virtual capacitance provided by the control is calculated using the small signal model and this verifies the effectiveness of the control quantitively and demonstrates that the small signal models are useful.

关键词： Resistance Capacitors Rectifiers Resonant converters Pulse width modulation control systems Generators Synchronous generators Wind turbines Oscillators

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Research on optimization of two-stage scheduling for aluminum extrusion machine manufacturing line

Research on optimization of two-stage scheduling for aluminu...

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2024 China Automation Congress, CAC 2024

作者： Zhou, Aoran Qiu, Lipeng Wu, Yali Department of Information and Control Engineering Xi'an University of Technology Shaan'xi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co Ltd Xi'an710016 China

ISBN: (纸本)9798350368604

In view of the problems of high energy consumption, long inventory time and low production efficiency in the production process of traditional aluminum extrusion machine, this paper establishes an efficient two-stage parallel scheduling optimization model based on the integration of flexible job shop scheduling and assembly sequence planning (IFJSS-ASP). On this basis, an evolutionary algorithm combining strong dominance relationship and simple grouping method (SDREA-SGM) is proposed. The algorithm utilizes a two-stage hybrid chromosome encoding and decoding method to establish a rational mapping from the decision space to the solution space. Furthermore, in order to prevent the model from easily falling into local optima, an adaptive intra-class and inter-class pairing selection strategy has been adopted by the algorithm. This enhances global search and improves local search ***, the feasibility and effectiveness of the algorithm are verified by solving problems of different scales. © 2024 IEEE.

关键词： Job shop scheduling

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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