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MASS FLOW DETECTION technology FOR SEED AND FERTILISER PARTICLES AND ITS APPLICATION IN UAV-BASED SPREADING

INMATEH - Agricultural Engineering 2025年第1期75卷 584-599页

作者： Wang, Yanshuang Song, Cancan Gao, Yongqi Lan, Yubin Wang, Guobin Ming, Rui College of Agricultural Engineering and Food Science Shandong University of Technology Zibo China Shandong University of Technology Sub-center of National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology Zibo China Research of Institute of Ecological Unmanned Farm Shandong University of Technology Zibo China School of Computer and Big Data Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China

The processes of sowing and fertiliser application represent a significant aspect of agricultural production. In order to achieve efficient and precise seeding and fertiliser application, mass flow detection of seed and fertiliser particles can facilitate real-time monitoring and precise decision-making for intelligent seeding and fertiliser application. However, the diversity of seed and fertiliser particle types and particle flow modes presents a challenge for existing detection methods, particularly in meeting the varying operational requirements, especially for particle mass flow detection in low-altitude and high-speed sowing operations of agricultural drones. In such cases, the overlap and flow rate will have a significant impact on the detection results due to the large displacement and the continuous high-throughput dense phase of the particle flow. This paper provides a summary of the existing seed and fertiliser particle mass flow detection techniques and their underlying working principles. It compares the direct detection based on mass with the indirect detection methods based on velocity and concentration, and analyses their respective advantages, disadvantages and applicability. It also explores the possibility of optimising the existing detection methods for the specific needs of agricultural UAVs and considers the potential introduction of cutting-edge science and technology in order to develop an efficient, accurate and convenient detection system to meet the growing market demand. © (2025), (INMA Bucharest). All Rights Reserved.

关键词： Precision agriculture

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Fed-Autoformer: A Federated Learning-Based Battery Anomaly Detection Approach for Electric Vehicle Charging with Privacy Preservation 30th

Fed-Autoformer: A Federated Learning-Based Battery Anomaly D...

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30th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2024

作者： Yan, Xuhan Yang, Shunbo Guo, Yiguo Fu, Yimu Wu, Sixing Li, Jianbin School of Control and Computer Engineering North China Electric Power University Beijing China Economic Technology Research Institute State Grid Shandong Electric Power Company Shandong Jinan City China

ISBN: (纸本)9783031829062

The battery management system ensures the safe operation of electric vehicles (EVs) by detecting abnormalities in the battery energy storage system. However, the extensive and widely dispersed data in EV battery data, along with the presence of users’ private details, raise a demand for effective anomaly detection and privacy protection. To tackle those two challenges, we propose Fed-Autoformer, a distributed anomaly detection architecture based on real vehicle charging data to detect battery anomalies and protect privacy. Thus, we first propose a novel anomaly detection model for EV charging data based on the Autoformer encoder architecture. In particular, it enables an autocorrelation attention mechanism to extract and consider the intrinsic correlation of battery data features (e.g., voltage, current, state of charge (SOC), etc.) for anomaly detection. In addition, we introduce a federated learning architecture to protect the privacy of battery charging data and improve the federated learning training process based on the differences between vehicle batteries in charging stations to ensure detection accuracy while protecting the privacy of EV charging data. Finally, we comprehensively analyze the feasibility and effectiveness of our proposed architecture using a real EV charging dataset. Our proposed federated learning approach for EV battery anomaly detection not only effectively protects privacy through federated learning but also improves the accuracy by 3.2% compared to most mainstream time series anomaly detection models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Charging stations

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Orthogonal projection-based regularization for efficient model augmentation

arXiv

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arXiv 2025年

作者： Györök, Bendegúz M. Hoekstra, Jan H. Kon, Johan Péni, Tamás Schoukens, Maarten Tóth, Roland Systems and Control Lab HUN-REN Institute for Computer Science and Control Budapest Hungary Control Systems Group Eindhoven University of Technology Netherlands Control Systems Technology Group Eindhoven University of Technology Netherlands

Deep-learning-based nonlinear system identification has shown the ability to produce reliable and highly accurate models in practice. However, these black-box models lack physical interpretability, and often a considerable part of the learning effort is spent on capturing already expected/known behavior due to first-principles-based understanding of some aspects of the system. A potential solution is to integrate prior physical knowledge directly into the model structure, combining the strengths of physics-based modeling and deep-learning-based identification. The most common approach is to use an additive model augmentation structure, where the physics-based and the machine-learning (ML) components are connected in parallel. However, such models are overparametrized, training them is challenging, potentially causing the physics-based part to lose interpretability. To overcome this challenge, this paper proposes an orthogonal projection-based regularization technique to enhance parameter learning, convergence, and even model accuracy in learning-based augmentation of nonlinear baseline models. © 2025, CC BY-NC-SA.

关键词： Contrastive Learning

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Learning for predictive control: A Dual Gaussian Process approach

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Automatica 2025年 177卷

作者： Liu, Yuhan Wang, Pengyu Tóth, Roland Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Flight Dynamics and Control Laboratory Department of Aerospace Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

An important issue in model-based control design is that an accurate dynamic model of the system is generally nonlinear, complex, and costly to obtain. This limits achievable control performance in practice. Gaussian Process (GP) based estimation of system models is an effective tool to learn unknown dynamics directly from input/output data. However, conventional GP-based control methods often ignore the computational cost associated with accumulating data during the operation of the system and how to handle forgetting in continuous adaption. In this paper, we present a novel Dual Gaussian Process (DGP) based Model Predictive control (MPC) strategy that enables efficient use of online learning based predictive control without the danger of catastrophic forgetting. The bio-inspired DGP structure is a combination of a long-term GP and a short-term GP, where the long-term GP is used to keep the learnt knowledge in memory and the short-term GP is employed to rapidly compensate unknown dynamics during online operation. A novel recursive online update strategy for the short-term GP is proposed to successively improve the learnt model during online operation without a "dictionary" update and re-computation of the Gram matrix at each time step. Effectiveness of the proposed strategy is demonstrated via numerical simulations. © 2025

关键词： Predictive control systems

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Automated Linear Parameter-Varying Modeling of Nonlinear Systems: A Global Embedding Approach

arXiv

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arXiv 2025年

作者： Olucha, E. Javier Koelewijn, Patrick J.W. Das, Amritam Tóth, Roland Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, an automated linear parameter-varying (LPV) model conversion approach is proposed for nonlinear dynamical systems. The proposed method achieves global embedding of the original nonlinear behavior of the system by leveraging the second fundamental theorem of calculus to factorize matrix function expressions without any approximation. The implementation of the proposed method in the LPVcore toolbox for Matlab is discussed, and its performance is showcased on a comprehensive example of automated LPV model conversion of an unbalanced disk system, which is then used to design an LPV controller that is deployed on the original nonlinear system. In addition, the conversion capabilities are further demonstrated by obtaining an LPV embedding of a three-degree-of-freedom control moment gyroscope. All software implementations are available at ***. © 2025, CC BY.

关键词： MATLAB

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Online Flow Scheduling in Virtualized Time-Sensitive Networks: A Joint Admission control and VNF Embedding Approach

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IEEE Transactions on Mobile Computing 2025年第6期24卷 4651-4667页

作者： Zhang, Yajing Chen, Cailian Li, Mingyan You, Chaoqun Guan, Xinping Quek, Tony Q. S. Shanghai Satellite Network Research Institute Co. Ltd. Shanghai200120 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Chongqing University College of Computer Science Chongqing400044 China Fudan University School of Computer Science Shanghai200433 China Singapore University of Technology and Design 487372 Singapore

Time-sensitive networking (TSN) is proposed to satisfy the increasingly stringent demands of Industrial 4.0 for deterministic transmission. This is achieved by generating a series of centrally configured gate control lists to strictly restrict the forwarding time of arriving flows. However, such a centralized scheme requires prior information of all flows, severely impeding TSN from providing an online response to dynamic industrial applications. To solve this problem, we innovatively propose to use admission control (AC) to realize deterministic transmission in the virtualized TSN network. In this approach, AC is distributively executed on each node and link, whereby flows of applications are served by passing through a series of virtual network functions (VNFs). This distributed AC execution is regarded as a VNF embedding (VNE) process. Specifically, we propose a two-stage online framework, Smart Admission control (SmartAC), to cater to dynamic applications. The first stage, referred to as the static stage, obtains a deterministic VNE solution by synthesizing AC decisions of individual TSN nodes and links. The second stage, referred to as the dynamic stage, fine-tunes VNE solutions obtained from the static stage to adapt to the harsh environment with insufficient resources or limited VNF migration budgets. Simulation results demonstrate the effectiveness of SmartAC in improving response rate and resource utilization ratio. Notably, SmartAC reduces runtime by 90% compared to existing algorithms and exhibits robustness across different network topologies. © 2002-2012 IEEE.

关键词： Budget control

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Motion planning for robotics:A review for sampling-based planners

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Biomimetic Intelligence & Robotics 2025年第1期5卷 15-34页

作者： Liding Zhang Kuanqi Cai Zewei Sun Zhenshan Bing Chaoqun Wang Luis Figueredo Sami Haddadin Alois Knoll School of Computation Information and Technology(CIT)Technical University of MunichMunich 85748Germany Munich Institute of Robotics and Machine Intelligence(MIRMI) Technical University of MunichMunich 80992Germany School of Control Science and Engineering Shandong UniversityJinan 250061China School of Computer Science University of NottinghamNottingham 315199United Kingdom

Recent advancements in robotics have transformed industries such as manufacturing,logistics,surgery,and planetary exploration.A key challenge is developing efficient motion planning algorithms that allow robots to navigate complex environments while avoiding collisions and optimizing metrics like path length,sweep area,execution time,and energy *** the available algorithms,sampling-based methods have gained the most traction in both research and industry due to their ability to handle complex environments,explore free space,and offer probabilistic completeness along with other formal *** their widespread application,significant challenges still *** advance future planning algorithms,it is essential to review the current state-of-the-art solutions and their *** this context,this work aims to shed light on these challenges and assess the development and applicability of sampling-based ***,we aim to provide an in-depth analysis of the design and evaluation of ten of the most popular planners across various *** findings highlight the strides made in sampling-based methods while underscoring persistent *** work offers an overview of the important ongoing research in robotic motion planning.

关键词： Robotics Motion planning Sampling-based algorithms

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Numerical Analysis of Optimal control of Assets and Liabilities by a Bank 4th

Numerical Analysis of Optimal Control of Assets and Liabi...

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4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： Zhukova, Aleksandra Flerova, Anna Chernov, Alexey Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Vavilov str 44 bld. 2 Moscow Russia Moscow Institute of Physics and Technology Institutki per. 9 Dolgoprudny141701 Russia

ISBN: (纸本)9783031812408

The formal description of the assets and liabilities management (ALM) by a bank within regulatory requirements leads to an optimal control problem with phase constraints. The phase constraints arise from the restrictions on banking activities, which are set by law to maintain the banking process. Solving such model explicitly is rarely possible, and numerical calculations enable to study its properties. The indirect method of the solution involves formulating the system of necessary optimality conditions and then computation of the ordinary differential equations system combined with specific equations for dual variables. This paper provides the details of application of the numerical methods and its specifics in the proposed economic model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Banking

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Computational imaging based on single-photon detection: a survey

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Artificial Intelligence Review 2025年第8期58卷 1-54页

作者： Pu, Yanyun Zhu, Chengyuan Yao, Gongxin Li, Chao Pan, Yu Yang, Kaixiang Yang, Qinmin State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China School of Computer Science and Engineering South China University of Technology Guangzhou China

The rapid advancements in single-photon detectors with picosecond timing resolution over the past decade have significantly driven the development of time-correlated single-photon counting (TCSPC) for computational imaging applications, including bioimaging and remote sensing. In this review, we utilize the CiteSpace tool to create knowledge maps and perform a bibliometric analysis of this research area. Furthermore, we provide a comprehensive overview of the key challenges associated with computational imaging using temporal single-photon counting. We also highlight how these challenges have been addressed under extreme conditions to establish a reference model for future imaging solutions. We examine the performance evaluation parameters of single-photon detectors to enhance the understanding of detector array scaling and their application in constructing efficient computational imaging systems. Lastly, we aim to elucidate the current technical challenges in single-photon detector-based computational imaging and explore their potential future developments.

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A third-party platoon coordination service: Pricing under government subsidies

A third-party platoon coordination service: Pricing under go...

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作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic control Society.

关键词： Trucks

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