Spatial-based iterative learning control for motion control applications

For many motion control applications spatial constraints are often more important than temporal constraints. In recent work, we have developed a spatial control strategy called the ε-controller for mobile robot applications. The control strategy is based solely on static path geometry with position (in space) feedback. Motivated by this idea, in this paper, we consider the notion of spatial-based iterative learning control (ILC). Specifically, we consider repetitive operation problems where corrections are made to the control signal from trial to trial. Unlike traditional ILC, however, which updates control signals based on the time elapsed along a trajectory, we instead make updates based on path errors and progress along the path. The idea is demonstrated via simulation for a system with bang–bang velocity control. Experimental results using a high-precision, two-axis gimbal mechanism are presented to show the effectiveness of the strategy.     

Regularization of Discontinuous Vector Fields on $${\mathbb{R}^3}$$ via Singular Perturbation

Singular perturbations problems in dimension three which are approximations of discontinuous vector fields are studied in this paper. The main result states that the regularization process developed by Sotomayor and Teixeira produces a singular problem for which the discontinuous set is a center manifold. Moreover, the definition of sliding vector field coincides with the reduced problem of the corresponding singular problem for a class of vector fields.      

基于粒子滤波的微小卫星姿态确定算法

为了提高非线性卫星姿态控制系统的滤波性能,在建立了采用磁强计及太阳敏感器的卫星姿态模型的基础上尝试了新兴的粒子滤波(PF)算法对卫星系统进行姿态估计,进而对采用矢量观测的三轴稳定卫星的姿态确定问题进行了滤波算法的实时仿真,并将四元数转换成旋转矢量引入了粒子滤波算法,最后给出了卫星模型在不同粒子数目下的滤波性能比较,并在系统初始误差较大的情况下将粒子滤波算法与EKF滤波算法进行了滤波性能的对照。仿真结果表明,粒子滤波算法对粒子数目具有明显的依赖性,但是当粒子达到一定的数目时,粒子滤波的精度以及滤波稳定性都可以得到保证,尤其是在系统初始误差较大的情况下粒子滤波算法更显示了其优于EKF算法的滤波性能。     

Explicit expression of polarization vector for surface waves,slip waves,Stoneley waves and interfacial slip waves in anisotropic elastic materials

We present explicit expression of the polarization vector for surface waves and slip waves in an anisotropic elastic half-space, and Stoneley waves and interfacial slip waves in two dissimilar anisotropic elastic half-spaces. An unexpected result is that, in the case of interfacial slip waves, the polarization vector for the material in the half-space _x2≥0$x_2\ge 0$ does not depend explicitly on the material property in the half-space _x2≤0$x_2\le 0$. It depends on the material property in the half-space _x2≤0$x_2\le 0$ implicitly through the interfacial slip wave speed υ$\upsilon$. The same is true for the polarization vector for the material in the half-space _x2≤0$x_2\le 0$.     

AUFS格式在无网格方法中的应用

将计算量小,激波分辨率高的AUFS (artificially upstream flux vector splitting) 格式应用于无网格方法. 所发展算法基于多项式基函数最小二乘无网格方法,采用线性基函数曲面拟合及AUFS 格式计算各离散点的空间导数,应用四阶Runge-Kutta 法进行时间显式推进. 为验证算法健壮性、精度以及计算效率,对Riemann 问题、超音速平面流动,以及不同攻角NACA0012 翼型跨音速流场进行了数值模拟,其结果同采用HLLC (Harten-Lax-van Leer-contact) 格式的无网格方法以及文献报道结果吻合较好,并且计算量较形式简单HLLC 格式减少约15%.     

柔性机构动态可靠性分析的新方法

为了改善柔性机构动态可靠性分析的效率和精度,基于支持向量机SVM(Support Vector Machine)回归理论,提出了一种柔性机构动态可靠性分析高效率高精度的SVM回归极值法SREM(SVM Regression Extremum Method)。首先,介绍了柔性机构可靠性分析的基本理论;其次,融合蒙特卡洛法MC(Monte Carlo)和SVM回归理论,建立了柔性机构动态响应极值的代理模型,并利用代理模型进行柔性机构可靠性分析。最后,利用SREM法对柔性机构实例进行了可靠性分析,并与MC和人工神经网络ANN(Artificial Neural Networks)的分析结果进行比较。结果显示,在小样本情况下,进行柔性机构动态可靠性分析时,SREM的计算效率和计算精度都比ANN高;SREM的计算效率比MC大大提高,计算精度与MC相当。验证了在柔性机构可靠性分析中SREM的高效率和高精度,并证明了SREM在柔性机构可靠性分析中的可行性和有效行性。     

Existence results for generalized vector equilibrium problems with applications

By a coincidence theorem, some existence theorems of solutions are proved for four types of generalized vector equilibrium problems with moving cones. Applications to the generalized semi-infinite programs with the generalized vector equilibrium constraints under the mild conditions are also given. The results of this paper unify and improve the corresponding results in the previous literature.     

基于激光雷达数据SVM分类的室内环境识别研究

语义地图构建对移动机器人导航与规划具有重要意义,而环境分类是语义地图构建的核心问题。目前所采用的环境分类方法匹配率较低,已成为语义地图构建所面临的主要问题。对此笔者提出了一种基于支持向量机的分类方法,该方法利用激光雷达数据提取环境几何特征,训练SVM分类器对机器人工作空间模式进行识别,并将所提算法用于室内环境的语义分类。实验结果表明,该分类方法具有较高的识别率,可有效地实现语义地图构建。     

基于梯度矢量流和主动轮廓模型的海陆边界提取

利用边缘检测与主动轮廓模型组合的方法可提取海陆边界线,但易受轮廓跟踪的缺点影响.在该方法的基础上,利用边缘检测与梯度矢量流的有向力作用生成初始轮廓线,再使用主动轮廓模型对初始轮廓线进行调整,得到精确的海陆边界.实验证明该方法可简便地生成有效的初始轮廓线并准确提取海陆边界,避免使用轮廓跟踪法.该方法可利用GIS数据辅助以简化提取流程.     

基于SVM的固化土无侧限抗压强度模型

为实现较少试验次数下固化土无侧限抗压强度(qu)的准确预测, 提出了基于支持向量机(SVM)的固化土qu的预测模型. 以固化剂各组分掺入比、龄期、初始含水量、固化剂掺量等因素为输入量, 固化土的qu作为输出量, 以径向基为核函数, 采用网格搜索法和交叉验证法进行参数优化, 建立了基于SVM的固化土qu的预测模型. 算例分析表明: 该模型适用于任意条件下固化土qu的精确预测, 且在较小试验成本下实现与响应面法相当的预测精度.