A nonlinear model of anti-backlash gear with time-varying friction and mesh stiffness was proposed for the further study on dynamic characteristics of anti-backlash gear. In order to improve the model precision, appli...A nonlinear model of anti-backlash gear with time-varying friction and mesh stiffness was proposed for the further study on dynamic characteristics of anti-backlash gear. In order to improve the model precision, applied force analysis was completed in detail, and single or double tooth meshing states of two gear pairs at any timing were determined according to the meshing characteristic of anti-backlash gear. The influences of friction and variations of damping ratio on dynamic transmission error were analyzed finally by numerical calculation and the results show that anti-backlash gear can increase the composite mesh stiffness comparing with the mesh stiffness of the normal gear pair. At the pitch points where the frictions change their signs, additional impulsive effects are observed. The width of impulsive in the same value of center frequency is wider than that without friction, and the amplitude is lower. When gear pairs mesh in and out, damping can reduce the vibration and impact.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
A new nonlinear transverse-torsional coupled model with backlash and bearing clearance was proposed for planetary gear set. Meanwhile, sun gear and planet's eccentricity errors, static transmission error, and time...A new nonlinear transverse-torsional coupled model with backlash and bearing clearance was proposed for planetary gear set. Meanwhile, sun gear and planet's eccentricity errors, static transmission error, and time-varying meshing stiffness were taken into consideration. The differential governing equations of motion were solved by employing variable step-size Rung-Kutta numerical integration method. The behavior of dynamic load sharing characteristics affected by the system parameters including input rate, sun gear's supporting stiffness and eccentricity error, planet's eccentricity error, sun gear's bearing clearance, backlashes of sun-planet and planet-ring meshes were investigated qualitatively and systematically. Some theoretical results are summarized at last which extend the current understanding of the dynamic load sharing behavior of planet gear train, enrich the related literature and provide references for the design of planetary gear train.展开更多
In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy...In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy is used to reconstruct the communication channel for the system that suffers from DoS attacks to prevent the discontinuous transmission information of the communication network from affecting MASs formation.Then,considering that the leader state is not available to each follower under DoS attacks,a fixed-time distributed observer without velocity information is constructed to estimate the tracking error between followers and the leader.Finally,adaptive radial basis function neural network(RBFNN) is used to approximate the unknown ensemble disturbances in the system,and the fixed-time time-varying formation scheme is designed with the constructed observer.The effectiveness of the proposed control algorithm is demonstrated by the numerical simulation.展开更多
开放世界目标检测(open world object detection,OWOD)的主要任务是检测已知类别和识别未知目标。此外,模型在下一个训练阶段中逐步学习已知新类。针对OW-DETR(open-world detection transformer)中未知类召回率偏低、密集目标与小目标...开放世界目标检测(open world object detection,OWOD)的主要任务是检测已知类别和识别未知目标。此外,模型在下一个训练阶段中逐步学习已知新类。针对OW-DETR(open-world detection transformer)中未知类召回率偏低、密集目标与小目标漏检等问题,提出了一种UBA-OWDT(UCSO,BiStrip and AFDF of open-world detection transformer)开放世界目标检测网络。针对未知类召回率偏低的问题,对未知类评分优化(unknown class scoring optimization,UCSO),将生成的浅层类激活图与聚合类激活图融合,获取细粒度特征信息,提高未知类的目标评分,进而提升未知类的召回率;针对小目标漏检问题,将双条状注意力(spatial attention based on strip pooling and strip convolution,BiStrip)应用于输入特征图,捕获长程依赖,保留目标精确的位置信息,增强感兴趣目标的表征,以检测小目标;针对密集目标漏检问题,采用自适应特征动态融合(adaptive feature dynamic fusion,AFDF),根据目标大小和形状,获得不同的感受野,动态分配注意力权重,关注目标的重要部分,融合不同层级的特征,以检测密集目标。在OWOD数据集的实验结果表明,未知类召回率增值范围在0.7~1.5个百分点,mAP增值范围在0.6~1.2个百分点,与现有的开放世界目标检测方法相比,在召回率偏低、密集目标与小目标漏检问题上具有一定的优势。展开更多
For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning...For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.展开更多
现有的基于深度学习模型的词嵌入方法用于Web异常检测时,通常将语料库中没有出现的未知词汇(Out of Vocabulary,OOV)设置为unknown,并赋予零或随机向量输入到模型中进行训练,未考虑未知词汇在Web请求语句中的上下文关系。同时,在Web系...现有的基于深度学习模型的词嵌入方法用于Web异常检测时,通常将语料库中没有出现的未知词汇(Out of Vocabulary,OOV)设置为unknown,并赋予零或随机向量输入到模型中进行训练,未考虑未知词汇在Web请求语句中的上下文关系。同时,在Web系统代码开发过程中,基于个人习惯并为了增加代码的可读性,程序员设计的请求路径代码往往存在一定的模式。因此,考虑到Web请求的模式和单词语义间的相关性,研究基于Word2vec的动态未知词表示方法DUWe(Dynamic Unknown Word Embedding),该方法通过分析Web请求路径中单词上下文的关系来赋予未知词向量的表示内容。在CSIC-2010和WAF Dataset数据集上的实验评估表明,增加未知词表示方法比仅用Word2vec静态特征提取方法具有更好的性能,同时在准确性、精准率、召回率和F1-Score方面均有提高,在训练时间上最大降低1.14倍。展开更多
基金Project(51175505)supported by the National Natural Science Foundation of China
文摘A nonlinear model of anti-backlash gear with time-varying friction and mesh stiffness was proposed for the further study on dynamic characteristics of anti-backlash gear. In order to improve the model precision, applied force analysis was completed in detail, and single or double tooth meshing states of two gear pairs at any timing were determined according to the meshing characteristic of anti-backlash gear. The influences of friction and variations of damping ratio on dynamic transmission error were analyzed finally by numerical calculation and the results show that anti-backlash gear can increase the composite mesh stiffness comparing with the mesh stiffness of the normal gear pair. At the pitch points where the frictions change their signs, additional impulsive effects are observed. The width of impulsive in the same value of center frequency is wider than that without friction, and the amplitude is lower. When gear pairs mesh in and out, damping can reduce the vibration and impact.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
基金Project(51105194)supported by the National Natural Science Foundation of ChinaProject(20113218110017)supported by the Doctoral Program Foundation of Institutions of Higher Education of China+2 种基金Project supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,ChinaProject(CXZZ11_0199)supported by the Funding of Jiangsu Innovation Program for Graduate Education,ChinaProjects(NZ2013303,NZ2014201)supported by the Fundamental Research Funds for the Central Universities,China
文摘A new nonlinear transverse-torsional coupled model with backlash and bearing clearance was proposed for planetary gear set. Meanwhile, sun gear and planet's eccentricity errors, static transmission error, and time-varying meshing stiffness were taken into consideration. The differential governing equations of motion were solved by employing variable step-size Rung-Kutta numerical integration method. The behavior of dynamic load sharing characteristics affected by the system parameters including input rate, sun gear's supporting stiffness and eccentricity error, planet's eccentricity error, sun gear's bearing clearance, backlashes of sun-planet and planet-ring meshes were investigated qualitatively and systematically. Some theoretical results are summarized at last which extend the current understanding of the dynamic load sharing behavior of planet gear train, enrich the related literature and provide references for the design of planetary gear train.
文摘In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy is used to reconstruct the communication channel for the system that suffers from DoS attacks to prevent the discontinuous transmission information of the communication network from affecting MASs formation.Then,considering that the leader state is not available to each follower under DoS attacks,a fixed-time distributed observer without velocity information is constructed to estimate the tracking error between followers and the leader.Finally,adaptive radial basis function neural network(RBFNN) is used to approximate the unknown ensemble disturbances in the system,and the fixed-time time-varying formation scheme is designed with the constructed observer.The effectiveness of the proposed control algorithm is demonstrated by the numerical simulation.
文摘开放世界目标检测(open world object detection,OWOD)的主要任务是检测已知类别和识别未知目标。此外,模型在下一个训练阶段中逐步学习已知新类。针对OW-DETR(open-world detection transformer)中未知类召回率偏低、密集目标与小目标漏检等问题,提出了一种UBA-OWDT(UCSO,BiStrip and AFDF of open-world detection transformer)开放世界目标检测网络。针对未知类召回率偏低的问题,对未知类评分优化(unknown class scoring optimization,UCSO),将生成的浅层类激活图与聚合类激活图融合,获取细粒度特征信息,提高未知类的目标评分,进而提升未知类的召回率;针对小目标漏检问题,将双条状注意力(spatial attention based on strip pooling and strip convolution,BiStrip)应用于输入特征图,捕获长程依赖,保留目标精确的位置信息,增强感兴趣目标的表征,以检测小目标;针对密集目标漏检问题,采用自适应特征动态融合(adaptive feature dynamic fusion,AFDF),根据目标大小和形状,获得不同的感受野,动态分配注意力权重,关注目标的重要部分,融合不同层级的特征,以检测密集目标。在OWOD数据集的实验结果表明,未知类召回率增值范围在0.7~1.5个百分点,mAP增值范围在0.6~1.2个百分点,与现有的开放世界目标检测方法相比,在召回率偏低、密集目标与小目标漏检问题上具有一定的优势。
基金supported by the National Natural Science Foundation of China(5110917951179156+2 种基金5137917661473233)the Natural Science Basic Research Plan in Shaanxi Province of China(2014JQ8330)
文摘For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.
文摘现有的基于深度学习模型的词嵌入方法用于Web异常检测时,通常将语料库中没有出现的未知词汇(Out of Vocabulary,OOV)设置为unknown,并赋予零或随机向量输入到模型中进行训练,未考虑未知词汇在Web请求语句中的上下文关系。同时,在Web系统代码开发过程中,基于个人习惯并为了增加代码的可读性,程序员设计的请求路径代码往往存在一定的模式。因此,考虑到Web请求的模式和单词语义间的相关性,研究基于Word2vec的动态未知词表示方法DUWe(Dynamic Unknown Word Embedding),该方法通过分析Web请求路径中单词上下文的关系来赋予未知词向量的表示内容。在CSIC-2010和WAF Dataset数据集上的实验评估表明,增加未知词表示方法比仅用Word2vec静态特征提取方法具有更好的性能,同时在准确性、精准率、召回率和F1-Score方面均有提高,在训练时间上最大降低1.14倍。
