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Extremum seeking control for UAV close formation flight via improved pigeon-inspired optimization

Science China(Technological Sciences) 2024年第2期67卷 435-448页

作者： yuan GuangSong DUAN HaiBin State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100083China

This paper proposes a comprehensive design scheme for the extremum seeking control(ESC)of the unmanned aerial vehicle(UAV)close formation *** proposed design scheme combines a Newton-Raphson method with an extended Kalman filter(EKF)to dynamically estimate the optimal position of the following UAV relative to the leading *** reflect the wake vortex effects reliably,the drag coefficient induced by the wake vortex is considered as a performance ***,the performance function is parameterized by the first-order and second-order terms of its Taylor series *** the excellent performance of nonlinear estimation,the EKF is used to estimate the gradient and the Hessian matrix of the parameterized performance *** output feedback of the proposed scheme is determined by iterative calculation of the Newton-Raphson *** with the traditional ESC and the classic ESC,the proposed design scheme avoids the slow continuous time integration of the *** allows a faster convergence of relative position ***,the proposed method can provide a smoother command during the seeking process as the second-order term of the performance function is taken into *** convergence analysis of the proposed design scheme is accomplished by showing that the output feedback is a supermartingale *** improve estimation performance of the EKF,a improved pigeon-inspired optimization(IPIO)is proposed to automatically tune the noise covariance *** Carlo simulations for a three-UAV close formation show that the proposed design scheme is robust to the initial position of the following UAV.

关键词： unmanned aerial vehicle close formation extremum seeking control Newton-Raphson method improved pigeon-inspired optimization

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Dynamic plugging regulating strategy of pipeline robot based on reinforcement learning

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Petroleum Science 2024年第1期21卷 597-608页

作者： Xing-yuan Miao Hong Zhao College of Mechanical and Transportation Engineering China University of PetroleumBeijing102249China

Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the pipeline and PIPR. In this paper, we propose a dynamic regulating strategy to reduce the plugging-induced vibration by regulating the spoiler angle and plugging velocity. Firstly, the dynamic plugging simulation and experiment are performed to study the flow field changes during dynamic plugging. And the pressure difference is proposed to evaluate the degree of flow field vibration. Secondly, the mathematical models of pressure difference with plugging states and spoiler angles are established based on the extreme learning machine (ELM) optimized by improved sparrow search algorithm (ISSA). Finally, a modified Q-learning algorithm based on simulated annealing is applied to determine the optimal strategy for the spoiler angle and plugging velocity in real time. The results show that the proposed method can reduce the plugging-induced vibration by 19.9% and 32.7% on average, compared with single-regulating methods. This study can effectively ensure the stability of the plugging process.

关键词： Pipeline isolation plugging robot Plugging-induced vibration Dynamic regulating strategy Extreme learning machine Improved sparrow search algorithm Modified Q-learning algorithm

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Realizing quantum imaginary time evolution in experiment

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Science China(Physics,Mechanics & Astronomy) 2024年第4期67卷 167-168页

作者： Xiao yuan Center on Frontiers of Computing Studies Peking UniversityBeijing 100871China School of Computer Science Peking UniversityBeijing 100871China

NISQ,or Noisy Intermediate-Scale Quantum computing,represents a pivotal and the state-of-the-art quantum technology[1].Characterized by intermediate-scale quantum devices that are beyond classical computational capabilities yet fall short of the error-correction thresholds required for fault-tolerant quantum computing,NISQ devices exhibit both promise and *** devices hold immense potential in solving certain computational problems that surpass classical capabilities,with wide applications in optimization,machine learning,and quantum chemistry.

关键词： quantum imaginary correction

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Global Spherically Symmetric Solutions for a Coupled Compressible Navier–Stokes/Allen–Cahn System

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Acta Mathematica Sinica,English Series 2024年第8期40卷 2037-2064页

作者： Chang Ming SONG Jian Lin ZHANG yuan yuan WANG Department of Applied Mathematics School of Mathematics and Information ScienceZhongyuan University of TechnologyZhengzhou 450007P.R.China

In this paper,we consider the global spherically symmetric solutions for the initial boundary value problem of a coupled compressible Navier–Stokes/Allen–Cahn system which describes the motion of two-phase viscous compressible *** prove the existence and uniqueness of global classical solution,weak solution and strong solution under the assumption of spherically symmetry condition for initial dataρ0 without vacuum state.

关键词： Diffuse interface model global solutions Navier-Stokes equations Allen-Cahn equation spherically symmetry

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Motor cortical circuit adaptations in parkinsonism

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Neural Regeneration Research 2024年第10期19卷 2107-2108页

作者： Hong-yuan Chu Department of Neurodegenerative Science Van Andel Research InstituteGrand RapidsMIUSA Aligning Science Across Parkinson’s(ASAP)Collaborative Research Network

Parkinson's disease is a chronic and progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta,which leads to the featured motor impairment of parki... 详细信息

关键词： parkin impairment rigidity

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A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

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Geodesy and Geodynamics 2024年第1期15卷 100-105页

作者： Fei Ye Yunbin yuan State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China Hunan Continuously Operating Reference Stations(HNCORS)Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame ***,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM ***,the weighted LS+AR hybrid method performs well for PM short-term ***,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR *** this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid *** using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid *** to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,***,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

关键词： Stochastic model LS+AR Short-term prediction The earth rotation parameter(ERP) Observation model

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MOF glass foam: a blueprint to porous membrane scaling-up

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Science China Chemistry 2024年第3期67卷 746-748页

作者： yuan Peng Weishen Yang State Key Laboratory of Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China

In comparison with conventional energy-intensive separation technologies, such as distillation and crystallization,membrane separation is labelled as an advanced technology with low energy consumption, a small carbon footprint,continuous operation, etc. Metal-organic frameworks(MOFs) are a burgeoning category of crystalline materials consisting of metal ions/clusters coordinated with organic ligands.

关键词： separation porous distillation

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特大型双排四点接触球轴承承载能力的研究

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机械工程学报 2014年第9期50卷 65-70页

作者：王燕霜袁倩倩曹佳伟李璞李燕河南科技大学机电工程学院洛阳471003

给出特大型双排四点接触球轴承承载曲线的精确计算方法.绘制其静承载曲面,并对精确静承载曲线及简化静承载曲线进行比较.分析轴承游隙、沟曲率半径系数及原始接触角对静承载曲线的影响.结果表明：随着轴承负游隙绝对值的增大,轴承所能... 详细信息

给出特大型双排四点接触球轴承承载曲线的精确计算方法.绘制其静承载曲面,并对精确静承载曲线及简化静承载曲线进行比较.分析轴承游隙、沟曲率半径系数及原始接触角对静承载曲线的影响.结果表明：随着轴承负游隙绝对值的增大,轴承所能承受的最大倾覆力矩增大,最大轴向力减小.游隙在-0.2～0 mm范围内取值,对轴承承载能力的影响较小.沟曲率半径系数对轴承承载能力影响较大,随着轴承沟曲率半径系数的增大,轴承静承载能力减小.随径向力增加,轴承承载能力随接触角增大先增大后减小.

关键词：特大型轴承四点接触承载能力

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Improved LS+MAR hybrid method to UT1-UTC ultra-short-term prediction by using first-order-difference UT1-UTC

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Geodesy and Geodynamics 2024年第4期15卷 379-385页

作者： Fei Ye Yunbin yuan BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha410007China State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan430077China HNCORS Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Accurate ultra-short-term prediction of the Earth rotation parameters(ERP)holds paramount impor-tance for real-time applications,particularly in reference frame *** them,diurnal rota-tion(UT1-UTC)which cannot be directly estimated through Global Navigation Satellite System(GNSS)techniques,significantly affects the rapid and ultra-rapid orbit determination of GNsS ***-ently,the traditional LS(least squares)+AR(autoregressive)and LS+MAR(multivariate autoregressive)hybrid methods stand as primary approaches for UT1-UTC ultra-short-term predictions(1-10 days).The LS+MAR hybrid method relies on the UT1-UTC and LOD(length of day)***,the correlation between LOD and first-order-difference UT1-UTC is stronger than that between LOD and *** light of this,and with the aid of the first-order-difference UT1-UTC,we propose an enhanced LS+MAR hybrid method to UT1-UTC ultra-short-term *** using the UT1-UTC and LOD data series of the IERS(International Earth Rotation and Reference Systems Service)EOP 14 C04 product,we conducted a thorough analysis and evaluation of the improved method's prediction performance compared to the traditional LS+AR and LS+MAR hybrid *** to the numerical results over more than 210 days,they demonstrate that,when considering the correlation information between the LoD and the first-order-difference UT1-UTC,the mean absolute errors(MAEs)of the improved LS+MAR hybrid method range from 21 to 934μs in 1-10 days *** comparison to the traditional LS+AR hybrid method,the MAEs show a reduction of 7-53μs in 1-10 days predictions,with corresponding improvement percentages ranging from 1 to 28%.Similarly,when compared to the traditional LS+MAR hybrid method,the MAEs have a reduction of 5-42μs in 1-10 days predictions,with corresponding improvement percentages ranging from 4-20%.Additionally,when aided by GNSS-derived LOD data series,the MAEs of improved LS+MAR hybrid method experience further

关键词： UT1-UTCultra-short-termprediction Rapidandultra-rapidproducts LS+AR and LS+MAR Correlation First-order-differenceUT1-UTC

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A regression approach for seismic first-break picking

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Petroleum Science 2024年第3期21卷 1584-1596页

作者： Huan yuan San-Yi yuan Jie Wu Wen-Jing Sang Yu-He Zhao CNPC Key Laboratory of Geophysical Exploration China University of Petroleum(Beijing)Beijing 102249China Research Institute of Petroleum Exploration&Development—Northwest(NWGI) Key Laboratory of reservoir characterization of CNPCPetroChinaLanzhou 730020GansuChina

The picking efficiency of seismic first breaks(FBs)has been greatly accelerated by deep learning(DL)***,the picking accuracy and efficiency of DL methods still face huge challenges in low signal-to-noise ratio(SNR)*** address this issue,we propose a regression approach to pick FBs based on bidirectional long short-term memory(Bi LSTM)neural network by learning the implicit Eikonal equation of 3D inhomogeneous media with rugged topography in the target *** employ a regressive model that represents the relationships among the elevation of shots,offset and the elevation of receivers with their seismic traveltime to predict the unknown FBs,from common-shot gathers with sparsely distributed *** from image segmentation methods which automatically extract image features and classify FBs from seismic data,the proposed method can learn the inner relationship between field geometry and *** addition,the predicted results by the regressive model are continuous values of FBs rather than the discrete ones of the binary *** picking results of synthetic data shows that the proposed method has low dependence on label data,and can obtain reliable and similar predicted results using two types of label data with large *** picking results of9380 shots for 3D seismic data generated by vibroseis indicate that the proposed method can still accurately predict FBs in low SNR *** subsequent stacked profiles further illustrate the reliability and effectiveness of the proposed *** results of model data and field seismic data demonstrate that the proposed regression method is a robust first-break picker with high potential for field application.

关键词： First-break picking Low signal-to-noiseratio Regression BiLSTM Traveltime Geometry Noisy seismic data

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