Creation of single-particle environment by positive dielectrophoresis and liquid dielectrophoresis

Two electrical mechanisms for manipulating particles and fluids, dielectrophoresis (DEP) and liquid dielectrophoresis (LDEP), are integrated in a microfluidic chip for creating the single-particle environment. The fluid is activated by LDEP with a 100-kHz/240-V_pp signal. When the single polystyrene bead approaches the trapping area, positive DEP force is utilized to capture and immobilize the bead. After trapping the bead, the process of liquid cutting and droplet creation is employed to create a droplet containing a single bead by LDEP with a 100-kHz/320-V_pp signal.     

混凝土结构温度内力数值分析

为研究混凝土结构的温度效应,利用ANSYS对混凝土框架、框架-剪力墙和剪力墙等结构在温度变化作用下的变形特点和内力分布规律进行系统分析.对具有不同纵向长度、楼层数和建筑体形特征的结构分别建立计算模型,在假设建筑物内外无温差和有温差两种温变条件下进行计算分析,从中得到各种结构温度变形和内力分布的基本规律,其主要结论对结构工程师具有实用价值.     

Continuous-flow particle and cell separations in a serpentine microchannel via curvature-induced dielectrophoresis

Particle and cell separations are critical to chemical and biomedical analyses. This study demonstrates a continuous-flow electrokinetic separation of particles and cells in a serpentine microchannel through curvature-induced dielectrophoresis. The separation arises from the particle size-dependent cross-stream dielectrophoretic deflection that is generated by the inherent electric field gradients within channel turns. Through the use of a sheath flow to focus the particle mixture, we implement a continuous separation of 1 and 5 μm polystyrene particles in a serpentine microchannel under a 15 kV/m DC electric field. The effects of the applied DC voltages and the serpentine length on the separation performance are examined. The same channel is also demonstrated to separate yeast cells (range in diameter between 4 and 8 μm) from 3 μm particles under an electric field as low as 10 kV/m. The observed focusing and separation processes for particles and cells in the serpentine microchannel are reasonably predicted by a numerical model.     

Behavior pattern extraction by trajectory analysis

Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through trajectory analysis. Firstly, we introduce directional trimmed mean distance (DTMD), a novel method used to measure similarity between trajectories. DTMD has the attributes of anti-noise, self-adaptation and the capability to determine the direction for each trajectory. Secondly, we use a hierarchical clustering algorithm to cluster trajectories. We design a length-weighted linkage rule to enhance the accuracy of trajectory clustering and reduce problems associated with incomplete trajectories. Thirdly, the motion model parameters are estimated for each trajectory’s classification, and behavior patterns for trajectories are extracted. Finally, the difference between normal and abnormal behaviors can be distinguished.     

Analytical formulation of electric field and dielectrophoretic force for moving dielectrophoresis using Fourier series

Electrokinetics manipulation and separation of living cells employing microfluidic devices require good knowledge of the strength and distribution of electric field in such devices. AC dielectrophoresis is performed by generating non-uniform electric field using microsize electrodes. Among the several applications of dielectrophoretic phenomenon, this present study considers the recently introduced phenomenon of moving dielectrophoresis. An analytical solution using Fourier series is presented for the electric field distribution and dielectrophoretic force generated inside a microchannel. The potential at the upper part of the microchannel has been found by solving the governing equation of the electric potential with specific boundary conditions. The solutions for the electric field and dielectrophoretic force show excellent agreement with the numerical results. Microdevices were fabricated and experiments were carried out with living cells confirming and validating the analytical solutions.     

基于书写力与字形信息的生物特征密钥生成

基于F-Tablet手写平台提出动态手写签名密钥生成方案,采用傅里叶变换提取特征,使用多态离散化算法生成稳定密钥,实现从动态手写签名到加密密钥的安全转换,并通过实验分析密钥生成方案的认证性能和安全性能.生成的密钥破译困难,随身携带,不会丢失被盗,不会增加用户的记忆负担,可用于身份认证、文件加密以及数字版权管理等领域.     

基于Simulink的拦截射网质点外弹道仿真分析

针对来袭弹体拦截手段单一,拦截成本高,拦截效率相对较低等问题,研发了一种新型的主动防护拦截射网。在威胁目标接近防护对象时,对来袭目标进行超近程拦截击爆。为更好地研究射网的射程及外弹道轨迹等相关飞行参数,进一步明确其防护拦截效能,采用MATLAB/Simulink对射网的外弹道方程进行仿真分析。考虑其空中飞行姿态的复杂性,故将射网简化为质点,利用质点外弹道方程进行仿真分析,通过常数模块、四则运算模块及积分模块等多种Simulink模块的配合,搭建射网飞行的质点外弹道仿真模型。将射网的仿真结果与理论分析结果进行对比,验证了仿真模型的有效性,为其他新研装备的仿真研究提供参考。     

乒乓球轨迹预测的研究与仿真

机器人打乒乓球时需要对快速运动的乒乓球的轨迹做出准确的预测。首先对乒乓球飞行轨迹预测中采用的运动学模型以及乒乓球碰撞的物理模型进行了分析,其次主要是对乒乓球飞行轨迹预测中采用的运动学模型的算法进行改进,速度反馈调节系数不再使用定值,而是采用动态系数。同时,反弹前的速度是通过对预测的轨迹用最小二乘法进行曲线拟合求导计算出来的。实验结果表明,预测效果很好。最后为了直观地分析预测轨迹,设计了基于OPENGL的3D仿真平台。     

带扩展记忆的粒子群优化算法仿真分析

从心理学的角度提出带扩展记忆的粒子群优化算法（PSOEM）,以克服标准粒子群优化算法（PSO）在优化多维函数过程中粒子搜索方向性差、目的性弱的缺陷.采用扩展记忆存储粒子的历史信息,并引入参数表征扩展记忆的重要性.利用经典离散控制理论分析其定值算法的稳定范围.此算法与标准算法是同源异构的,可以与已改进的PSO算法结合使用.基准测试函数的仿真结果验证了所提出算法的有效性.     

移动机械手运动/力鲁棒自适应轨迹跟踪

针对移动机械手控制器设计中用隐函数定理进行模型降阶时存在的一些问题,把完整和非完整约束的统一形式引入到系统的动力学模型降阶中．基于该降阶模型设计了不确定移动机械手稳定的运动／力鲁棒自适应线性参数模糊控制器．理论分析和仿真结果表明,设计的控制器简单有效．     

Set point trajectory and internal force control in redundant dual-arm manipulation

A nonlinear decoupling and linearizing feedback control is considered for dynamic coordination of two planar robot arms manipulating an object. A general inverse dynamics-based method is presented that assures an exact feedback linearization for simultaneous control of the object trajectory on the plane and internal efforts transmitted from the robot end-effectors to the object. The method takes the manipulator dynamics and object dynamics into consideration. A method for parameterizing the grip matrix null space is proposed, which has formed a basis for developing a new method for calculating the internal efforts. The procedure is invariant with respect to the change of the torque origin and units of length, and provides the force distribution without internal squeezing effects. A comparison between the approaches known so far and the new method is presented. No previously published method assures noninvariance and nonsqueezing properties for all possible contact configurations. Control algorithms are developed for a system of robotic arms that has more degrees of freedom than necessary for given tasks, exhibiting both actuation and kinematic redundancy. The implementation of this method is demonstrated for the case of a system of two planar three-link arms with the end-effectors manipulating an object, with different constrained task configurations. Practical aspects of discrete-time inverse dynamics control, such as influence of the computational time delay and robustness to model imperfections, are discussed. It is demonstrated that it is possible to achieve high-precision tracking of object position and internal force profiles, even if a system imperfect model is used for controller design. © 1993 John Wiley & Sons, Inc.     

Automated clustering of trajectory data using a particle swarm optimization

Clustering trajectory data discovers and visualizes available structure in movement patterns of mobile objects and has numerous potential applications in traffic control, urban planning, astronomy, and animal science. In this paper, an automated technique for clustering trajectory data using a Particle Swarm Optimization (PSO) approach has been proposed, and Dynamic Time Warping (DTW) distance as one of the most commonly-used distance measures for trajectory data is considered. The proposed technique is able to find (near) optimal number of clusters as well as (near) optimal cluster centers during the clustering process. To reduce the dimensionality of the search space and improve the performance of the proposed method (in terms of a certain performance index), a Discrete Cosine Transform (DCT) representation of cluster centers is considered. The proposed method is able to admit various cluster validity indexes as objective function for optimization. Experimental results over both synthetic and real-world datasets indicate the superiority of the proposed technique to fuzzy C-means, fuzzy K-medoids, and two evolutionary-based clustering techniques proposed in the literature.     

非均匀分布颗粒群中的曳力分布

本文采用格子Boltzmann方法(LBM)在图形处理器(GPU)上计算了由静止圆柱阵列组成的团聚物周期单元内的不可压缩流体流动,流固交界面处采用直接反弹以实现无滑移边界,每个圆柱上的曳力通过统计动量交换直接求得。根据LBM求得的流体速度,对于团聚物中的单圆柱按能量最小多尺度(EMMS)模型计算平均曳力系数,并考察了将聚团近似为均匀悬浮的临界条件。对颗粒雷诺数Re_p在0～10之间的80种固相份额的模拟结果表明,密相空隙率可以表征这种临界条件。当固相份额恒定时,该临界空隙率随着Re_p的增加而降低;当Re_p恒定时,该临界空隙率随着固相份额的增加而降低。     

Tuning of evolutionary particle filtering approach for estimation of trajectory deviation

An autonomous vehicle launched from moving platform is subjected to flexure‐like disturbance and needs to stabilize itself before embarking on the target tracking phase. Control and guidance remains inactive during stabilization phase. Hence, estimating the deviation from the intended trajectory is important in the absence of control and guidance commands for trajectory correction. This estimation problem is here mapped to the misalignment estimation problem, with the intended trajectory data resembling mother data and the followed trajectory data resembling daughter data. The main requirement is fast convergence for early commencement of target tracking phase. Kalman filter and its variants fail to converge due to the inability to model time varying nonlinearities and flexure in the system model. Conventional particle filter converges, but computation time is high. This work explores evolutionary particle filter variants that may provide faster convergence through adaptive tuning of the range from where particle support points are selected. Such heuristics is based on the observed residual trend. Monte Carlo simulation results underline the importance of designing estimator based on adaptive tuned evolutionary particle filter algorithm.     

微加速度开关吸附力仿真计算

研究了平面度对微加速度开关触点形貌的影响,建立了触点吸附物理模型,根据微观连续介质理论推导出触点间包含斥力项的吸附力数学模型,经仿真得到吸附力随触点间隙的非线性变化规律,并得到最大吸附力,从而为微加速度开关的结构设计和系统分析提供理论基础。     

On trajectory and force tracking control of constrained mobile manipulators with parameter uncertainty

This paper studies the trajectory and force tracking control problem of mobile manipulators subject to holonomic and nonholonomic constraints with unknown inertia parameters. Adaptive controllers are proposed based on a suitable reduced dynamic model, the defined reference signals and the mixed tracking errors. The proposed controllers not only ensure the entire state of the system to asymptotically converge to the desired trajectory but also ensure the constraint force to asymptotically converge to the desired force. A detailed numerical example is presented to illustrate the developed methods.     

Adaptive trajectory control of microcantilever's tip utilised in atomic force microscopy-based manipulation

This article presents a hybrid distributed-parameters model and an adaptive control framework for microcantilevers utilised in atomic force microscope systems for controlled force manipulations. The model assumes a general nonlinear interaction force between the microcantilever's tip and the surface of the sample. This interaction force includes the sample's surface and probe's tip distance as well as the first and second derivatives of this force implicitly. Despite such detailed modelling of interaction force, there are a number of uncertainties including tip mass, damping coefficients and nature of the interaction force that would affect the response of the system and hence, an adaptive controller is needed to compensate for these unmodelled dynamics and uncertainties. Unlike the current practices that deal with the lumped-parameters model of the cantilever, a comprehensive distributed-parameters model based on the Euler–Bernoulli theory is considered here. An adaptive controller is then designed such that by giving a force input to the base of the microcantilever, the tip of the microcantilever can track a desired trajectory despite the flexibility of the microcantilever and aforementioned uncertainties. Extensive simulation results are provided to illustrate that the microcantilever's tip can asymptotically follow a harmonic trajectory even for a system with higher modes of vibration when it is designed based on single-mode model.     

A trajectory analysis of near aggregation

The basic idea of aggregation is that there exists a reduced-order model such that, for an appropriate initial condition, the trajectories of the reduced-order model are linear combinations of the trajectories of the full-order model. The authors study systems which do not aggregate exactly, but which `nearly aggregate'. It is shown that for nearly aggregable systems, there exists a reduced-order model such that, for an appropriate initial condition, the trajectories of the reduced-order model are near a linear combination of the trajectories of the full-order model