Ho∞-based fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay

The fault detection problem for the nonlinear networked control system (NCS) with packet dropout and delay is investigated.A nonlinear stochastic system model is proposed to account for the NCS with random packet dropout and networkinduced non-uniformly distributed time-varying delay in both from sensor to controller (S/C) and from controller to actuator (C/A).Based on the obtained NCS model,employing an observer-based fault detection filter as the residual generator,the addressed fault detection problem is converted into an auxiliary nonlinear H∞ control problem.Then,with the help of Lyapunov functional approach,a sufficient condition for the desired fault detection filter is constructed in terms of certain linear matrix inequalities,which depend on not only the delay interval but also the delay interval occurrence rate and successful packet communication rate.Especially,a trade-off phenomenon between the maximum allowable delay bound and successful data packet transmission rate is found,which is typically resulted from the limited bandwidth of communication networks.The effectiveness of the proposed method is demonstrated by a simulation example.     

H_∞-based fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay

The fault detection problem for the nonlinear networked control system(NCS) with packet dropout and delay is investigated.A nonlinear stochastic system model is proposed to account for the NCS with random packet dropout and networkinduced non-uniformly distributed time-varying delay in both from sensor to controller(S/C) and from controller to actuator(C/A).Based on the obtained NCS model,employing an observer-based fault detection filter as the residual generator,the addressed fault detection problem is converted into an auxiliary nonlinear H∞ control problem.Then,with the help of Lyapunov functional approach,a sufficient condition for the desired fault detection filter is constructed in terms of certain linear matrix inequalities,which depend on not only the delay interval but also the delay interval occurrence rate and successful packet communication rate.Especially,a trade-off phenomenon between the maximum allowable delay bound and successful data packet transmission rate is found,which is typically resulted from the limited bandwidth of communication networks.The effectiveness of the proposed method is demonstrated by a simulation example.     

表面增强拉曼散射光谱同时检测4种痕量多环芳烃

合成了植酸保护的纳米金,其具有较强的疏水性和表面增强拉曼散射(SERS)活性.利用小型拉曼光谱仪和分子光谱的指纹信息特征,建立可同时分析水中多种多环芳烃的SERS分析方法.多环芳烃检出限如下:蒽为100μg/L,荧蒽为100μg/L,芘达到10μg/L和苯并芘可达1μg/L.     

数字图像连续表示及应用

研究了离散图像的连续表示及重建问题.首先利用弦理论,给出了图像的连续表示形式,然后利用付里叶变换实现了图像连续表示及重建的快速算法,接着将它们应用于图像无级缩放、图像平滑、边缘检测、角点检测,并与传统离散图像处理方法的实验结果进行了比较.实验结果表明:利用图像连续表示方法处理离散图像可以得到不差于传统的离散图像处理方法处理的结果,此方法使离散图像的解析法处理成为可能.     

对象迁移自动机在TDT中的聚类研究

对象迁移自动机(OMA)是一种能够较好地解决话题识别与跟踪(TDT)中聚类问题的方法,但是,传统OMA模型由于聚类速度慢等缺点,难以满足TDT实时和增量聚类的要求.针对这一问题,本文一方面改进传统的OMA模型中自动机的动作设计,同时提出文档选择策略,加快了OMA的聚类速度.改进的方法在中等文档集上进行了实验,实验结果表明,该方法具有较好的聚类效果.     

一种并联机构结构误差识别与修正的新算法

为了提高并联机床的运动精度,针对简化误差源模型（含42个误差量）,基于并联机构位置正解的快速算法提出了一种结构误差识别的新算法．首先按理论并联机构设计参数,将一球杆仪的两个球铰分别固定在保持平行的动、静平台上,令球杆仪在动平台上的球铰中心相对于静平台上的球铰中心做球面螺旋线运动．然后在此前提下根据球杆仪球杆理论计算长度与实际长度之差构造m维矢量空间,依次让每一个待识别的结构参数有一个单位增量,重点修正与实测误差相关程度最高的结构参数．并通过从测量误差向量中分离出主修正向量后的残余误差向量方法提高修正效率．经过若干轮修正,直到使修正后球杆理论计算长度与实际长度基本一致,即可认为各项误差已修正完毕．该算法只需测量球杆的长度值,大大减少了测量工作量及由此而引入的误差源．     

基于A*改进算法的机械臂避障路径规划

为解决机械臂在运行时可能与工作空间中的障碍物发生碰撞,提出圆柱体包络碰撞检测法和基于A*算法的变步长分段搜索法.运用圆柱体包络碰撞检测法,将碰撞检测问题转化为计算圆柱体间的位置关系.变步长分段搜索法解决了应用传统A*算法可能出现的搜索数据量大甚至搜索死循环等问题.分别在基于OpenGL的三维仿真实验平台和实际系统中验证了该方法的有效性和可行性.     

基于模糊梯度的微齿轮图像边缘检测算法

提出一种基于模糊梯度思想的微齿轮图像边缘检测算法.该算法采用正切归一化函数对灰度图像模糊化,并计算该模糊图像的梯度矩阵;采用正弦函数对梯度矩阵进一步模糊化得到模糊梯度矩阵;采用基于归一化实数编码的遗传算法来搜索最优的阈值λ对模糊梯度矩阵做截集,获取图像边缘点集合.实验中以不同微齿轮图像作为实验对象,测试了该算法性能.实验结果表明,该算法的检测精度优于10μs,检测时间基本为1s,整体性能优于Canny算法和Pal-King算法.     

大型高功率激光装置下装系统的碰撞检测

分析了大型高功率激光装置在线可替换单元装校过程的特殊性,建立了基于区域划分的下装系统的方向包围盒,在包围盒的计算中引入闵可夫斯基和的概念,并在其基础上对分离轴的选择进行优化组合,结合碰撞的局部性原理,构建了一种动态的OBB(Oriented Bounding Box)层次树检测方法,经过中国大型高功率激光装置下装系统的装校仿真实践,结果表明这种划分区域的连续检测方法高效可靠。     

基于GMM和MRF的自适应阴影检测

运动目标阴影在很大程度上会影响运动目标跟踪、行为识别的正确性和有效性.为此,文中提出了一种基于混合高斯模型和马尔科夫随机场的自适应阴影检测方法.该方法首先对混合高斯模型进行改进,使其可以自适应调整参数学习率以消除浅阴影;然后采用马尔科夫随机场综合邻域的空间依赖性信息进行精确的阴影检测.为了提高基于马尔科夫随机场的阴影检...