【目的】在空间超冗余机械臂动力学建模中,其结构复杂、自由度多及刚性弱导致的动力学耦合问题十分突出,难以获得精准的动力学模型。针对此问题,提出了一种应用迭代WLS-TCS算法的空间超冗余机械臂地面动力学参数辨识方法,为获取机械臂...【目的】在空间超冗余机械臂动力学建模中,其结构复杂、自由度多及刚性弱导致的动力学耦合问题十分突出,难以获得精准的动力学模型。针对此问题,提出了一种应用迭代WLS-TCS算法的空间超冗余机械臂地面动力学参数辨识方法,为获取机械臂的高精度动力学模型和空间在轨动力学控制研究奠定基础。【方法】首先,采用一种基于终端交叉和转向的粒子群优化(Terminal Crossover and Steering-based Particle Swarm Optimization,TCS-PSO)算法来设计满足多约束条件的周期傅里叶级数,并将其作为最优的激励轨迹;其次,应用迭代加权最小二乘(Iterative Weighted Least Squares,IWLS)法获取最小参数集,通过迭代加权逐步剔除数据中的异常值,使得辨识结果更加鲁棒、准确。【结果】试验结果表明,在激励轨迹中,采用TCS优化方法获得的轨迹回归矩阵条件数更少,且能更好满足所给的约束条件。在参数辨识中,采用IWLS法辨识所得的结果对比递归最小二乘法,力矩残差均方根(Root Mean Square,RMS)值平均降低约2.22%;对比加权最小二乘法,力矩残差RMS值平均降低约4.85%。将获取的参数模型代入到零力控制试验中,实际效果符合预期。展开更多
This paper develops a variational model for image noise removal using total curvature(TC), which is a high-order regularizer. The TC has the advantage of preserving image feature. Unfortunately, it also has the charac...This paper develops a variational model for image noise removal using total curvature(TC), which is a high-order regularizer. The TC has the advantage of preserving image feature. Unfortunately, it also has the characteristics of nonlinear, non-convex and non-smooth. Consequently, the numerical computation with the curvature regularization is difficult. In order to conquer the computation problem, the proposed model is transformed into an alternating optimization problem by importing auxiliary variables. Furthermore, based on alternating direction method of multipliers, we design a fast numerical approximation iterative scheme for proposed model. Finally, numerous experiments are implemented to indicate the advantages of the proposed model in image edge preserving, image contrast and corners preserving. Meanwhile, the high computational efficiency of the designed model is verified by comparing with traditional models, including the total variation(TV) and total Laplace(TL) model.展开更多
By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting ...By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting sort while maintaining the original stability. Compared with the original counting sort, it has a wider scope of application and better time and space efficiency. In addition, the accuracy of the above conclusions can be proved by a large amount of experimental data.展开更多
相位细分技术是提高精密仪器测量分辨率和精度的关键技术。传统的机械、光学等细分技术已难以满足当前高精度测量领域的需求。基于坐标旋转数字计算(Coordinate Rotation Digital Computer,CORDIC)方法的角度计算原理,将输入的正交信号...相位细分技术是提高精密仪器测量分辨率和精度的关键技术。传统的机械、光学等细分技术已难以满足当前高精度测量领域的需求。基于坐标旋转数字计算(Coordinate Rotation Digital Computer,CORDIC)方法的角度计算原理,将输入的正交信号转换为向量(x,y),通过多次旋转迭代使向量最终收敛于X轴,对旋转角度进行求和即可得到目标角度值。基于FPGA用Verilog语言编写CORDIC算法,可以实现相位细分、信号辨向和整周期计数功能,通过扩展数据位宽消除了算法迭代过程中产生的舍入误差。对改进算法进行了仿真与实验验证,结果表明经过20级迭代后其理论分辨率为0.4″,计算角度的误差为±0.5″,光栅测角系统实际测量误差减小了约98.42%。该算法通过对正交信号进行精密细分来计算精密仪器的相角变化量,在工程应用中具有普适性。展开更多
Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has b...Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.展开更多
在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流...在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流计数法,以获取光伏并网功率指令;利用小波包分解确定电池组数量及容量,同时根据设计的充、放电原则形成电池组的功率调节指令;进行电池组组别重置时,将BESS中诸多电池单元进行有序分配;提出二次功率分配策略,获取各电池单元的功率调节指令,二次分配时还应用了重复补发原则以最大限度跟踪功率调节指令,并保证组内电池单元荷电状态均衡。对所提功率分配方法进行了仿真验证,并与其他5种策略进行了对比,结果表明,所提功率分配方法实现了BESS对于功率调节指令的更好跟踪,降低了光伏并网功率波动率,延长了电池单元的使用寿命。展开更多
驱动力控制系统(Traction Control System,TCS)是在制动防抱死系统的基础上发展起来的一套主动安全控制系统,它根据汽车的行驶状况,通过采用适当的控制算法使汽车驱动轮在恶劣路面或复杂行驶条件下也能产生最佳的纵向驱动力,从而提高汽...驱动力控制系统(Traction Control System,TCS)是在制动防抱死系统的基础上发展起来的一套主动安全控制系统,它根据汽车的行驶状况,通过采用适当的控制算法使汽车驱动轮在恶劣路面或复杂行驶条件下也能产生最佳的纵向驱动力,从而提高汽车的驱动性能和行驶稳定安全性能。通过对TCS控制原理的分析,明确滑转率的控制目标,结合TCS的控制方式,阐述TCS的常用控制算法,并对其进行比较,探讨TCS控制算法的选择依据和方法。展开更多
文摘【目的】在空间超冗余机械臂动力学建模中,其结构复杂、自由度多及刚性弱导致的动力学耦合问题十分突出,难以获得精准的动力学模型。针对此问题,提出了一种应用迭代WLS-TCS算法的空间超冗余机械臂地面动力学参数辨识方法,为获取机械臂的高精度动力学模型和空间在轨动力学控制研究奠定基础。【方法】首先,采用一种基于终端交叉和转向的粒子群优化(Terminal Crossover and Steering-based Particle Swarm Optimization,TCS-PSO)算法来设计满足多约束条件的周期傅里叶级数,并将其作为最优的激励轨迹;其次,应用迭代加权最小二乘(Iterative Weighted Least Squares,IWLS)法获取最小参数集,通过迭代加权逐步剔除数据中的异常值,使得辨识结果更加鲁棒、准确。【结果】试验结果表明,在激励轨迹中,采用TCS优化方法获得的轨迹回归矩阵条件数更少,且能更好满足所给的约束条件。在参数辨识中,采用IWLS法辨识所得的结果对比递归最小二乘法,力矩残差均方根(Root Mean Square,RMS)值平均降低约2.22%;对比加权最小二乘法,力矩残差RMS值平均降低约4.85%。将获取的参数模型代入到零力控制试验中,实际效果符合预期。
基金supported by the National Natural Science Foundation of China(No.61602269)the China Postdoctoral Science Foundation(No.2015M571993)+1 种基金the Shandong Provincial Natural Science Foundation of China(No.ZR2017MD004)the Qingdao Postdoctoral Application Research Funded Project
文摘This paper develops a variational model for image noise removal using total curvature(TC), which is a high-order regularizer. The TC has the advantage of preserving image feature. Unfortunately, it also has the characteristics of nonlinear, non-convex and non-smooth. Consequently, the numerical computation with the curvature regularization is difficult. In order to conquer the computation problem, the proposed model is transformed into an alternating optimization problem by importing auxiliary variables. Furthermore, based on alternating direction method of multipliers, we design a fast numerical approximation iterative scheme for proposed model. Finally, numerous experiments are implemented to indicate the advantages of the proposed model in image edge preserving, image contrast and corners preserving. Meanwhile, the high computational efficiency of the designed model is verified by comparing with traditional models, including the total variation(TV) and total Laplace(TL) model.
文摘By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting sort while maintaining the original stability. Compared with the original counting sort, it has a wider scope of application and better time and space efficiency. In addition, the accuracy of the above conclusions can be proved by a large amount of experimental data.
文摘相位细分技术是提高精密仪器测量分辨率和精度的关键技术。传统的机械、光学等细分技术已难以满足当前高精度测量领域的需求。基于坐标旋转数字计算(Coordinate Rotation Digital Computer,CORDIC)方法的角度计算原理,将输入的正交信号转换为向量(x,y),通过多次旋转迭代使向量最终收敛于X轴,对旋转角度进行求和即可得到目标角度值。基于FPGA用Verilog语言编写CORDIC算法,可以实现相位细分、信号辨向和整周期计数功能,通过扩展数据位宽消除了算法迭代过程中产生的舍入误差。对改进算法进行了仿真与实验验证,结果表明经过20级迭代后其理论分辨率为0.4″,计算角度的误差为±0.5″,光栅测角系统实际测量误差减小了约98.42%。该算法通过对正交信号进行精密细分来计算精密仪器的相角变化量,在工程应用中具有普适性。
基金support of the Natural Science Foundation of Jiangsu Province,China(BK20240977)the China Scholarship Council(201606850024)+1 种基金the National High Technology Research and Development Program of China(2016YFD0701003)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(SJCX23_1488)。
文摘Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.
文摘在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流计数法,以获取光伏并网功率指令;利用小波包分解确定电池组数量及容量,同时根据设计的充、放电原则形成电池组的功率调节指令;进行电池组组别重置时,将BESS中诸多电池单元进行有序分配;提出二次功率分配策略,获取各电池单元的功率调节指令,二次分配时还应用了重复补发原则以最大限度跟踪功率调节指令,并保证组内电池单元荷电状态均衡。对所提功率分配方法进行了仿真验证,并与其他5种策略进行了对比,结果表明,所提功率分配方法实现了BESS对于功率调节指令的更好跟踪,降低了光伏并网功率波动率,延长了电池单元的使用寿命。
文摘驱动力控制系统(Traction Control System,TCS)是在制动防抱死系统的基础上发展起来的一套主动安全控制系统,它根据汽车的行驶状况,通过采用适当的控制算法使汽车驱动轮在恶劣路面或复杂行驶条件下也能产生最佳的纵向驱动力,从而提高汽车的驱动性能和行驶稳定安全性能。通过对TCS控制原理的分析,明确滑转率的控制目标,结合TCS的控制方式,阐述TCS的常用控制算法,并对其进行比较,探讨TCS控制算法的选择依据和方法。
