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IEEE Transactions on Intelligent Vehicles 2024年第11期9卷 1-13页

作者： Liang, Hongjing Yang, Shoufeng Li, Tieshan Zhang, Huaguang School of Automation Engineering University of Electronic Science and Technology of China Chengdu China College of Control Science and Engineering Bohai University Jinzhou China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

This paper focuses on the distributed adaptive cooperative control problem for human-in-the-loop (HiTL) heterogeneous unmanned aerial vehicle-unmanned ground vehicle (UAV-UGV) systems via an improved prescribed performance approach. A novel human motion recognition system (HMRS) is designed and integrated into the HiTL strategy. Specifically, the leader trajectory can be changed in real time based on HMRS and the leader signal library to cope with various unexpected situations. This HiTL strategy solves the discontinuity and non-differentiability problems that may exist before and after human modification of leader signals within the extremely short time in conventional HiTL strategies. Moreover, an improved predefined-time prescribed performance approach is proposed, in which the performance function only needs to be first-order continuous differentiable instead of infinite-order continuous differentiable. This approach can greatly broaden the selection range of performance functions. Furthermore, a unified model of heterogeneous UAV-UGV systems is established to avoid designing UAV and UGV systems separately, which improves the universality of the control algorithm. Finally, the proposed HiTL control scheme is applied to a simulation example to verify its feasibility and effectiveness. IEEE

关键词： Intelligent vehicle highway systems

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Development of Motion Analysis Tool for Orthopedic Diseases: Inertial Measurements 6th

Development of Motion Analysis Tool for Orthopedic Diseases:...

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6th Computational Methods in Systems and Software, CoMeSySo 2022

作者： Jicinsky, Pavel Mares, Jan Department of Process Control Faculty of Electrical Engineering and Informatics University of Pardubice Pardubice Czech Republic

ISBN: (纸本)9783031214349

Rehabilitation in orthopedics is one of the most important processes that influence the patient’s quality of life. In today’s practice, the orthopedic assessments still depend mainly on subjective view of physician. To further objectify the results, a wearable electronic device was developed based on inertial sensors. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： IMU Motion analysis Orthopedics Signal acquisition and processing

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Real-time power flow analysis and management for a long-endurance solar UAV during continuous flight

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CEAS Aeronautical Journal 2023年第4期14卷 1035-1049页

作者： Ghelem, Nourddine Boudana, Djamel Bouchhida, Ouahid Laboratory of Process Control LCP Department of Engineering Control Systems and Applied Mathematics National Polytechnic School ENP of Algiers 10 St Hacen Badi El Harrach Algiers Algeria Department of Electrical Engineering LREA Laboratory University of Medea Medea Algeria

One of the primary challenges for Unmanned Aerial Vehicle (UAV) developers is to improve their endurance while in the air, as their typical flight time is limited to a few hours. One widely used technology to enhance their endurance is harnessing solar energy to power UAV and charge their batteries in flight. This article presents the development of a real-time simulation environment to enable the continuous flight of the Sky Sailor solar UAV. Through the utilization of a solar irradiance model, a solar panel model, real-time power generation is calculated. Simultaneously, the UAV’s full dynamic model, along with the autopilot and propulsion system model, is employed to determine the energy consumption at each moment. The energy management algorithm then compares the acquired energy with the power consumed, and in cases of surplus energy, it is efficiently stored in the battery for nighttime usage. Simulations show that continuous flight of the drone can be achieved during the summer season, when the daylight hours are long enough to fully charge the battery, With the ability to fly continuously during this period, the UAV can be used in various areas, such as monitoring forest fires, agricultural fields, beaches, and security monitoring for oil companies and their life bases in deserts. © 2023, Deutsches Zentrum für Luft- und Raumfahrt e.V.

关键词： Solar energy

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Robustness of gross primary production estimation from long-term reconstructed solar-induced chlorophyll fluorescence varies with greenness on a global scale

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Journal of Applied Remote Sensing 2025年第1期19卷

作者： Fu, Lijiang Xia, Qian Tang, Hao Chen, Junqing Tan, Jinglu Guo, Ya Jiangnan University Ministry of Education Key Laboratory of Advanced Process Control for Light Industry Wuxi China Changshu Institute of Technology School of Electrical Engineering and Automation Changshu China University of Missouri Department of Chemical and Biomedical Engineering ColumbiaMO United States

Long-term reconstructed solar-induced chlorophyll fluorescence (SIF) derived from raw gridded SIF has been used for the estimation of gross primary production (GPP), but the robustness of the spatial relationship may vary from location to location. We examined the often-used linear relationship between GPP and SIF in terms of R2 values for varied locations globally using three GPP datasets (FLUXCOM, VPM, PML) and three long-term reconstructed monthly SIF datasets (CSIF, SIF005, and RTSIF). The results show that the R2 value is a concave function of vegetation greenness level (NDVI) on an annual or seasonal basis. The average R2 is over 0.8 in areas where the annual average NDVI is in the range of 0.4 to 0.6, whereas the R2 is much lower where the annual average NDVI is less than 0.2 or greater than 0.8. Prediction of GPP or SIF by three methods from five major environmental variables revealed greater uncertainties in GPP and/or SIF at low or high greenness levels as an apparent cause of the low R2. The results offer useful insights into how global GPP may be effectively estimated from multi-satellite measured SIF. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Optical correlation

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Parameter estimation in solar power plant systems: a comparative study of recursive and iterative techniques

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Sustainable Energy Research 2024年第1期11卷 1-12页

作者： Sadeghi, Kiavash Hossein Shafikhah, Mahmood Marashian, Arash Roshandel, Emad Razminia, Abolhassan Department of Electrical Engineering Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran Process Control Laboratory Faculty of Natural Sciences and Engineering Åbo Akademi University Turku Finland College of Science and Engineering Flinders University Adelaide Australia

The development of a dynamic model for a popular implemented solar power plant is a critical task for power engineers aiming to enhance the plant’s performance and reliability. In this study, we utilized the prediction error method (PEM), a robust algorithm for system identification, to capture the plant’s operational characteristics with precision. Additionally, we employed both recursive and hierarchical algorithms to identify the system parameters effectively. The results from each identification method are rigorously quantified and analyzed, allowing for a detailed comparison of their performance. This comprehensive evaluation not only highlights the strengths and weaknesses of each approach, but also provides valuable insights into their practical applications in the context of solar power systems. © The Author(s) 2024.

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FedAWS: A Federated Tuning Approach with Adaptive Weight Shrinking for Pre-trained Foundation Models 13

FedAWS: A Federated Tuning Approach with Adaptive Weight Shr...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Cheng, Yubin Song, Zhihuan Jiang, Xiaoyu Yao, Le Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control College of Control Science and Engineering Hangzhou310027 China School of Mathematics Hangzhou Normal University Hangzhou China

ISBN: (纸本)9798350361674

In recent years, pre-trained foundation models have developed rapidly and have been applied to various downstream tasks through fine-tuning methods. However, due to the existence of data silos, the lack of data for fine-tuning has become a vital issue preventing the application of the foundation model to industry. In addition, the high complexity of the network makes the foundation model prone to overfitting when used for data-constrained industrial tasks. Therefore, a federated tuning approach with adaptive weight shrinking, named FedAWS, is proposed for collaborative fine-tuning between factories. FedAWS adaptively selects the weight-shrinking factor to reduce overfitting and improve the generalization of the global model without relying on additional data sets or human experience. The case study on an industrial dataset demonstrates the effectiveness of FedAWS. This successful validation provides a new way for inter-factory collaboration to apply the foundation model to industry, thus facilitating the efficient utilization of industrial data. © 2024 IEEE.

关键词： Federated Learning Fine-tuning Foundation Model Weight Shrinking

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Identify the objective parameters of direct communication between PLC and MS SQL server 24

Identify the objective parameters of direct communication be...

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24th International Carpathian control Conference, ICCC 2023

作者： Flaga, Stanislaw Majcher, Maciej AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Process Control Krakow Poland

ISBN: (纸本)9798350310221

When building digital twins of existing technical solutions, we need a large amount of data on the parameters of their operation under various conditions. The source of data on the values of process variables at the lowest level is control devices - most often PLCs. There are many ways to acquire the qualities of process variables available from the PLC level. Increasingly, OPC UA is replacing the OPC model, and the OPC UA server is increasingly a functionality of the PLC CPU. The Industrial Internet of Things IIoT is used in companies moving toward Factory 4.0. Data from controllers can be acquired using high-level languages such as C++, C# or Python. Libraries often made available under an open-source license are used for this. For example, you can find commercial libraries for communication between PLCs of selected manufacturers and MySQL servers. Siemens provides a library for communication between S7-1200/1500 controllers and MS SQL server. The author has yet to find an exhaustive analysis of such a solution. In the literature, there need to be more studies of experiments describing the performance of query generation and execution and the impact of the library on PLC performance. The article presents the results of an experimental study of this issue. © 2023 IEEE.

关键词： Libraries

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Research study of image classification algorithms based on Convolutional Neural Networks 24

Research study of image classification algorithms based on C...

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24th International Carpathian control Conference, ICCC 2023

作者： Nawrocka, Agata Nawrocki, Marcin Kot, Andrzej AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Process Control Krakow Poland

ISBN: (纸本)9798350310221

The beginning of the paper introduces the idea of neural networks by presenting the neuron models and artificial neural networks. Next, the flow of operations used in the development of convolutional neural networks is presented, as well as an overview of popular architectures used in model development. After introducing the theoretical issues, a project using the EfficientNet architecture to recognize medical images taken by MRI is presented. The project describes: the selection and parameters of the MRI image database representing different types of brain tumors, the process of implementation and appropriate modification of the EfficientNet architecture used to classify images, the presentation of the results of learning the convolutional neural network and the images that highlight on the basis of which area the convolutional neural network classifies images. © 2023 IEEE.

关键词： Convolutional neural networks

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Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1239-1249页

作者： Ke Li Shunyi Zhao Biao Huang Fei Liu Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan UniversityWuxi 214122China Department of Chemical and Materials Engineering University of AlbertaEdmonton AB T6G 2G6Canada

In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensionality,and directly exploiting holistic information for state inference is not always computationally *** paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear *** high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense *** that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state ***,the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing *** results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

关键词： filtering estimation error

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Recovery of cathode copper and ternary precursors from CuS slag derived by waste lithium-ion batteries:process analysis and evaluation

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Chinese Chemical Letters 2024年第7期35卷 178-182页

作者： Yun Wei Lei Zhou Wenbin Hu Liming Yang Guang Yang Chaoqiang Wang Hui Shi Fei Han Yufa Feng Xuan Ding Penghui Shao Xubiao Luo National-Local Joint Engineering Research Center of Heavy Metals Pollutants Control and Resource Utilization Nanchang Hangkong UniversityNanchang 330063China School of Life Science Jinggangshan UniversityJi’an 343009China CAS Key Laboratory of Green Process and Engineering National Engineering Research Center of Green Recycling for Strategic Metal ResourcesInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China Biomass Molecular Engineering Center and Anhui Provincial Key Laboratory of Microbial Pest Control Anhui Agricultural UniversityHefei 230036China Jiangxi Ganfeng Recycling Technology Co.LTD. Xinyu 338004China

The efficient and environmentally friendly recycling technology of waste residue that including abundant heavy metal produced during the recovery of lithium batteries has become a research ***,a novelty process of acid leaching-selective electrodeposition-deep impurity removal-regeneration was proposed to recovery of the CuS slag,which has been efficient transferred to high purity cathode copper and commercially available ternary *** cathode with a purity of 99.67%was prepared under electrochemical reaction conditions at-0.55 V for 2 h.A novel impurity remover-Mn powder,which was used to remove the residual impurities and as a feedstock for the ternary ***,NCM523 was regenerated by *** process is superior to the traditional process in economy,energy consumption,CO_(2)emissions,product purity and process *** study provides a new approach for solid waste recovery and precious metal enrichment.

关键词： CuS slag Electrodeposition Cathode copper Ternary precursor Solid waste recovery

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