Nonlinear oscillations of sigmoid functionally graded material plates moving in longitudinal direction

Geometrically nonlinear oscillations are investigated on sigmoid functionally graded material （S-FGM） plates with a longitudinal speed. The material properties of the plates obey a sigmoid distribution rule along the thickness direction. Based on the D＇Alembert＇s principle, a nonlinear equation of motion is derived for the moving S-FGM plates, where the von K^rm^n nonlinear plate theory is adopted. Utilizing the Galerkin method, the equation of motion is discretized and solved via the method of harmonic bal- ance. The approximate analytical solutions are validated through the adaptive step-size fourth-order Runge-Kutta method. Besides, the stability of the steady-state solutions is examined. The results reveal that the mode interaction behavior can happen between the first two modes of the moving S-FGM plates, leading to a complex nonlinear frequency response. It is further found that the power-law index, the longitudinal speed, the exci- tation amplitude, and the in-plane pretension force can significantly affect the nonlinear frequency-response characteristics of longitudinally traveling S-FGM plates.

Applications of An Eddy-Viscosity Eliminator Based on Sigmoid Functions in Reynolds-Averaged Navier-Stokes Simulations of Sloshing Flow

Reynolds-averaged Navier-Stokes(RANS)turbulence modeling can lead to the excessive turbulence level around the interface in two-phase flow,which causes the unphysical motion of the interface in sloshing simulation.In order to avoid the unphysical motion of the interface,a novel eddy-viscosity eliminator based on sigmoid functions is designed to reduce the excessive turbulence level,and the eddy-viscosity eliminator based on polynomials is extracted from the cavitation simulations.Surface elevations by combining the eddy-viscosity eliminators and classical two-equation closure models are compared with the experiments,the ones by using the adaptive asymptotic model(AAM)and the ones by using the modified two-equation closure models.The root-mean-squared error(RMSE)is introduced to quantify the accuracies of surface elevations and the forces.The relation between the turbulence level in the transition layer and RMSEs of surface elevations is studied.Besides,the parametric analysis of the eddy-viscosity eliminators is carried out.The studies suggest that(1)the excessive turbulence level in the transition layer around the interface has a significant influence on the accuracies of surface elevations and the forces;(2)the eddy-viscosity eliminators can effectively reduce the excessive turbulence level in the transition layer to avoid the unphysical motion of the interface;(3)the k-ωSST model combined with the eddy-viscosity eliminators is appropriate for predicting surface elevations and forces in RANS simulations of sloshing flow.

Improved parameter identification algorithm for ship model based on nonlinear innovation decorated by sigmoid function

This paper investigates the problem of parameter identification for ship nonlinear Nomoto model with small test data,a nonlinear innovation-based identification algorithm is presented by embedding sigmoid function in the stochastic gradient algorithm.To demonstrate the validity of the algorithm,an identification test is carried out on the ship‘SWAN’with only 26 sets of test data.Furthermore,the identification effects of the least squares algorithm,original stochastic gradient algorithm and the improved stochastic gradient algorithm based on nonlinear innovation are compared.Generally,the stochastic gradient algorithm is not suitable for the condition of small test data.The simulation results indicate that the improved stochastic gradient algorithm with sigmoid function greatly increases its accuracy of parameter identification and has 14.2%up compared with the least squares algorithm.Then the effectiveness of the algorithm is verified by another identification test on the ship‘Galaxy’,the accuracy of parameter identification can reach more than 95%which can be used in ship motion simulation and controller design.The proposed algorithm has advantages of the small test data,fast speed and high accuracy of identification,which can be extended to other parameter identification systems with less sample data.

Fuzzy adaptive learning control network with sigmoid membership function

To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.

基于AHP耦合Sigmoid函数的重载铁路黄土边坡风险分析

重载铁路具有大轴重、高密度、大运量的运输特点,黄土边坡路基段一直是重载铁路运营的高风险区段,现有风险评价方法尚无法满足其风险量化分析的需求。利用层次分析法AHP耦合Sigmoid函数的方法,围绕事故发生概率和损失两个方面对重载铁路黄土边坡工程展开风险定量评价。首先以边坡滑塌事故调研和稳定性控制理论为基础,明确黄土边坡的失稳影响因素,建立重载铁路黄土边坡稳定性评价模型和边坡失稳危害性评价模型;然后应用层次分析法建立黄土边坡稳定性评价模型指标权重,并提出各级影响因素的指标赋值方法;而后引入基于朴素贝叶斯理论的Sigmoid函数,构建边坡稳定服役概率、风险判断矩阵和黄土边坡的风险等级确定方法;最后以朔黄铁路某站高陡黄土边坡为工程背景,应用所得理论方法对其进行风险定量分析,计算得出该边坡失稳概率为0.64,造成经济损失约8611万元,隶属于高风险等级,并针对坡体几何特征、渗透能力、基岩特性等低分指标提出了具体的安全性提升措施建议。

Constructive Approximation by Superposition of Sigmoidal Functions

In this paper, a constructive theory is developed for approximating func- tions of one or more variables by superposition of sigmoidal functions. This is done in the uniform norm as well as in the L^p norm. Results for the simultaneous approx- imation, with the same order of accuracy, of a function and its derivatives （whenever these exist）, are obtained. The relation with neural networks and radial basis func- tions approximations is discussed. Numerical examples are given for the purpose of illustration.

DEGREE OF APPROXIMATION BY SUPERPOSITIONS OF A SIGMOIDAL FUNCTION

In this paper we study the degree of approximation by superpositions of a sigmoidal function.We mainly consider the univariate case.If f is a continuous function,we prove that for any bounded sigmoidal function σ,d_(n,σ)(f)≤‖σ‖ω(f,1/(n+1)).For the Heaviside function H(x),we prove that d_(n,H)(f)≤ω(f,1/(2(n+1))). If f is a continuous funnction of bounded variation,we prove that d_(n,σ)(f)≤‖σ‖/(n+1)V(f)and d_(n,H)(f)≤ 1/(2(n+1))V(f).For he Heaviside function,the coefficient 1 and the approximation orders are the best possible.We compare these results with the classical Jackson and Bernstein theorems,and make some conjec- tures for further study.

基于Sigmoid函数的非对称式S型曲线机械臂加减速控制方法

机械臂广泛应用于制造、装配、搬运、码垛等方面,对提高生产力起着重要作用。为减小机械臂在运动过程中的振动和冲击,提高机械臂轨迹执行效率,提出一种非对称式S型曲线加减速控制方法。该方法通过在双段Sigmoid函数中插入直线段,构成加加速度连续的运动学曲线。通过粒子群算法进行参数优化求解,无需反复确认每个时间段的存在性即可求出非对称约束下的曲线参数,并分别在关节空间和笛卡尔空间采用时间同步和位移同步方法使机械臂的运动轨迹更加协调自然。结果表明,相同条件下提出的方法比三角函数方法轨迹执行效率更高且加加速度仅为三角函数方法的55%。与梯形加加速度曲线相比,采用提出的方法规划的运动轨迹可减少35.7%的残余振动,验证了该方法的有效性。

脉冲噪声下基于Sigmoid的LFM信号参数估计

由于脉冲噪声具有的短时大幅值特性,使得基于高斯假设的信号参数估计方法无法在脉冲噪声环境下有效估计参数。针对此问题,利用α稳定分布模拟随机脉冲噪声,提出了一种基于Sigmoid-CFRFT的LFM信号参数估计方法。首先,建立了一种自适应Sigmoid函数,证明了信号经过此非线性变换后,信号的2阶矩由无界变为有界,且信号的相位信息保持不变。其次,将变换后的信号进行离散时间CFRFT,建立了数学优化模型,并使用水循环算法搜索最优值点。最后,利用了非标准SαS分布噪声的修正方法,分析了标准和非标准分布下参数估计的性能。仿真结果说明,所提方法不仅可以有效抑制脉冲噪声对LFM信号分数谱特征的影响,而且能够实现低信噪比信号参数的高精度估计。相比于现有的基于非线性变换的参数估计方法,本文方法具有更好的精度,稳定性和噪声鲁棒性。

基于改进型sigmoid函数的混合储能系统SOC控制策略

介绍锂离子电池-超级电容混合储能系统的传统SOC控制策略,提出一种基于改进型sigmoid函数的SOC控制策略,并通过算例来展示混合储能模型的构建、仿真过程,分析验证基于改进型sigmoid函数的混合储能系统SOC控制策略的有效性。

Evaluation of the Effect of Sigmoid-Shaped Interventricular Septum on Left Ventricular Systolic Function in Patients with Essential Hypertension by Two-Dimensional Speckle Tracking Echocardiography

Objective: To evaluate left ventricular regional and global systolic function by measuring left ventricular longitudinal strain (LS) in hypertensive patients with sigmoid-shaped interventricular septum (SIS) by two-dimensional speckle tracking (2D-STE);in order to explore whether the sigmoid-shaped interventricular septum affects the left ventricular systolic function in patients with hypertension. Methods: Routine echocardiographic parameters were measured in 30 hypertensive patients with SIS (SIS group) and 30 hypertensive patients without SIS (non-SIS group). The left ventricular segments and global LS were measured by 2D-STE, and the two sets of parameters were compared. Results: The value of the thickness of the basal segment of the interventricular septum (IVSBT), the thickness of the middle segment of the interventricular septum (IVSMT) and the ratio of the basal segment of the ventricular septum to the middle segment of the interventricular septum (IVSBT/IVSMT) in SIS group was higher than that in non-SIS group. However, the value of left ventricular outflow tract diameter (LVOTD) in SIS group was lower than that in non-SIS group. There was a significant difference between the two groups (all P Conclusion: SIS affects left ventricular regional systolic function of patients with hypertension. 2D-STE can early evaluate left ventricular longitudinal systolic function in hypertensive patients with SIS.

基于Sigmoid函数拟合的亚像素边缘检测方法

亚像素边缘检测技术是采用图像处理软件算法来提高检测精度的有效途径,文中对矩法、拟合法和插值法等常用的亚像素边缘检测算法的原理、优点和不足进行了分析,提出了Sigmoid函数拟合的亚像素边缘定位算法.该算法采用Sigmoid函数拟合边缘模型,利用图像边缘灰度信息对模型进行非线性最小二乘拟合,求得边缘的亚像素位置.理论分析和实验结果表明,基于Sigmoid函数拟合的亚像素边缘定位算法的定位精度为0.045像素,但检测的速度比灰度矩提高了一个数量级,比空间矩、Zern ike矩和插值法提高了两个数量级.此算法能较好地满足影像测量的稳定可靠、高精度及强实时性要求.

水下机器人基于sigmoid函数的软变结构控制

针对水下机器人滑模变结构控制系统抖振问题,利用具有光滑性和饱和性的sigmoid函数,提出一种水下机器人软变结构控制策略。利用Lyapunov稳定性理论,讨论控制受限情形的水下机器人软变结构控制系统的稳定性,构造基于sigmoid函数的软变结构控制器,给出水下机器人软变结构控制的具体算法。将基于sigmoid函数的软变结构控制策略用于水下机器人仿真实验研究,实验结果验证了该方法的可行性和有效性。与线性控制、饱和线性控制和基于变饱和函数的软变结构控制3种控制方法进行对比仿真分析,分析结果表明,基于sigmoid函数设计的软变结构控制系统调节精确度高、响应速度快,有效地削弱了系统抖振,具有良好的动态性能。

一种基于Sigmoid函数的改进协同过滤推荐算法

随着电子商务和社交网络的蓬勃发展,推荐系统逐渐成为数据挖掘领域的重要研究方向。推荐系统能够从海量信息中定位用户兴趣点,提供个性化服务。协同过滤算法能够有效分析用户偏好,提供合适的推荐服务。针对评分矩阵稀疏时传统协同过滤算法性能很差的问题,提出一种基于Sigmoid函数的改进推荐系统算法。利用Sigmoid函数对不同项目进行建模,得到项目的平均受欢迎程度;利用Sigmoid函数对不同用户进行建模,将评分映射为用户对项目的喜好程度;根据用户对项目喜好程度应该与项目平均受欢迎程度贴近的原则进行评分预测。在两组真实数据集合上的实验结果表明,该算法较好地解决了数据稀疏性问题,能够有效提高传统算法的预测准确性。

基于sigmoid函数激励需求响应模型的电动汽车有序充电控制策略

基于经济学理论提出电动汽车有序充电电价模型,给出考虑负荷波动和电动汽车车主支出最小为目标的多目标函数,利用蒙特卡罗方法模拟车主的充电行为,最后,采用粒子群算法求解多目标函数;该方法在电价激励机制的控制过程中,加入用户对电价的响应环节,给出满足sigmoid函数的电价激励策略在不同激励陡度参数下对电动汽车充电的引导效果。以某地区为例进行有序充电场景仿真模拟,结果表明:在兼顾车主和充电站运营商利益前提下,电动汽车规模一定时,选择适合的激励陡度参数能改善负荷曲线,使电网负荷波动最小。

Sigmoid函数的分段非线性拟合法及其FPGA实现

使用分段非线性逼近算法计算超越函数,以神经网络中应用最为广泛的Sigmoid函数为例,结合函数自身对称的性质及其导数不均匀的特点提出合理的分段方法,给出分段方式同逼近多项式阶数对逼近结果精度的影响。完成算法在FPGA上的硬件实现,给出一种使用三阶多项式处理Sigmoid函数的拟合结果及流水线架构,处理精度达到10-5数量级,最大频率达到127.327 MHz,满足了高速、高精度的处理要求。

基于权值与结构确定法的单极Sigmoid神经网络分类器

构造了以单极Sigmoid函数作为隐层神经元激励函数的神经网络分类器,网络中输入层到隐层的权值和隐层神经元的阈值均为随机生成。同时,结合利用伪逆思想一步计算出隐层和输出层神经元之间连接权值的权值直接确定(WDD)法,进一步提出了具有边增边删和二次删除策略的网络结构自确定法,用来确定神经网络最优权值和结构。数值实验结果表明,该算法能够快速有效地确定单极Sigmoid激励函数神经网络分类器的最优网络结构;分类器的分类性能良好。

利用Sigmoid函数表征超低渗透储层的非达西渗流特征

达西渗流产水率模型已难以准确描述超低渗透储层的产液性能,为了准确表征超低渗透储层的产液能力,必须基于非达西渗流特征建立高精度产水率模型.神经元非线性函数Sigmoid的突变性质能较好地描述非达西渗流特征,并可以通过改变系数来控制其突变时间和幅度,因此,引入该函数来构建超低渗透储层的产水率模型.在超低渗透储层,压裂改造措施破坏了油藏状态下含水饱和度与产水率之间的关系;计算方法和实验分析所携带的误差造成计算含水饱和度与油藏状态下含水饱和度之间存在数值差异.分类弥补这一差异之后,利用Sigmoid函数建立的产水率模型计算97口井的产水率,与实际压裂试油的产液数据进行对比分析,相关系数为0.900 4,满足研究区实际勘探开发生产需求.

基于改进sigmoid函数的非线性跟踪微分器

本文受神经网络中常用的sigmoid激励函数特性的启发,提出了一种形式简单、调参相对容易的非线性跟踪微分器(STD).首先,在sigmoid函数的基础上引入指数和幅度因子,利用改进后的sigmoid函数构造加速度函数,接着,借助Lyapunov直接法证明了所设计的跟踪微分器的非摄动形式具有全局渐近稳定性,随后利用系统等价性给出了跟踪微分器的具体形式并通过扫频测试分析了其频域特性;最后,与线性微分器(LD)、全程快速跟踪微分器(HSTD)以及改进的跟踪微分器(ITD)、反正切形式的跟踪微分器(ATD)分别进行对比仿真分析.结果表明,基于sigmoid函数设计的跟踪微分器可以兼顾响应的快速性以及平稳性、全程无抖振,对信号的广义导数具有良好的逼近能力和滤波效果.

基于Sigmoid函数的PMSM滑模变结构位置速度观测器

针对永磁同步电机无速度传感器控制系统,设计了新的滑模观测器进行转子位置和速度的观测。在通常滑模电流观测器基础上引入反电势估测值,构造了新滑模观测器,采用Sigmoid函数代替常数切换函数在一定程度上减小抖振,采用变截止频率低通滤波器,代替常用低通滤波器,使电机相位补偿是一个常数。通过李亚普诺夫稳定性定理证明了设计的滑模变结构观测器的渐进稳定性。通过仿真和实验验证了设计的滑模控制器,证实了其有效性和可行性。