Finite time control of robotic manipulators with position output feedback

This paper deals with the robust finite time tracking of desired trajectories for a wide group of robotic manipulators in spite of unknown disturbances, uncertainties, and saturations of actuators while only manipulator's positions are available and its velocities are not measurable physically. A new form of chattering‐free second order fast nonsingular terminal sliding mode control scheme is introduced to design input torques for fulfilling the determined tracking objective in the adjustable total finite settling time. The proposed control algorithm is incorporated with two nonlinear observers to estimate disturbances and velocities of joints within finite settling times. The global finite time stability of the closed‐loop manipulator is analytically proved. Finally, a numerical simulation is carried out to verify the effectiveness of the designed input torques. Copyright © 2017 John Wiley & Sons, Ltd.     

基于快速模板匹配的智能视觉传感器设计*

针对传统视觉传感器信号处理能力差、模拟信号输出易受干扰等问题,设计了基于ARM 6410处理器的智能化数字视觉传感器,应用于白车身在线视觉检测系统,完成数据采集、像素级二维定位和通讯控制工作。在Linux平台上,研究了一种快速稳定的像素级模板匹配算法,以去均值归一化灰度互相关法为相似性测度,多分辨率金字塔匹配法为搜索策略,使用“滚动相加补全像素法冶的二维求和新方法来优化计算过程,并进行了全局冗错设计,确保传感器工作稳定性。现场实验表明：采用该匹配算法和冗错机制使得视觉传感器定位功能速度快、精度高、鲁棒性好,能较好完成白车身视觉检测系统前端数据采集和处理任务。     

基于伪码自相关特性与三次样条插值的GPS信号快速捕获算法

提出了一种新的基于伪码自相关特性和三次样条捅值拟合方法的GPS信号快速捕获算法.首先通过低频采样序列依据循环相关法求得C/A码相位粗略值;然后根据C/A码相位粗略值得到用于二次捕获的高频采样部分序列,利用伪码自相关特性求得精确C/A码相位值;最后利用三次样条插值法处理相关谱谱峰及邻近数据以进一步提高C/A码相位的测量精度.仿真结果表明该算法具有精度高、运算量小的优点.     

一种基于密度的快速聚类算法

聚类是数据挖掘领域中的一个重要研究方向,聚类技术在统计数据分析、模式识别、图像处理等领域有广泛应用,迄今为止人们提出了许多用于大规模数据库的聚类算法。基于密度的聚类算法DBSCAN就是一个典型代表。以DBSCAN为基础,提出了一种基于密度的快速聚类算法。新算法以核心对象领域中所有对象的代表对象为种子对象来扩展类,从而减少区域查询次数,降低I/O开销,实现快速聚类,对二维空间数据测试表明：快速算法能够有效地对大规模数据库进行聚类,速度上数倍于已有DBSCAN算法。     

Mathematical Morphology Based on Linear Combined Metric Spaces on Z2 (Part I): Fast Distance Transforms

Mathematical Morphology (MM) is a general method for image processing based on set theory. The two basic morphological operators are dilation and erosion. From these, several non linear filters have been developed usually with polynomial complexity, and this because the two basic operators depend strongly on the definition of the structural element. Most efforts to improve the algorithm's speed for each operator are based on structural element decomposition and/or efficient codification.A new framework and a theoretical basis toward the construction of fast morphological operators (of zero complexity) for an infinite (countable) family of regular metric spaces are presented in work. The framework is completely defined by the three axioms of metric. The theoretical basis here developed points out properties of some metric spaces and relationships between metric spaces in the same family, just in terms of the properties of the four basic metrics stated in this work. Concepts such as bounds, neighborhoods and contours are also related by the same framework.The presented results, are general in the sense that they cover the most commonly used metrics such as the chamfer, the city block and the chess board metrics. Generalizations and new results related with distances and distance transforms, which in turn are used to develop the morphologic operations in constant time, in contrast with the polynomial time algorithms are also given.     

The generalized unified computation of multidimensional discrete orthogonal transforms

By introducing a form of reorder for multidimensional data, we propose a unified fast algo-rithm that jointly employs one-dimensional W transform and multidimensional discrete polynomial trans-form to compute eleven types of multidimensional discrete orthogonal transforms, which contain three types of m-dimensional discrete cosine transforms ( m-D DCTs) ,four types of m-dimensional discrete W transforms ( m-D DWTs) ( m-dimensional Hartley transform as a special case), and four types of generalized discrete Fourier transforms ( m-D GDFTs). For real input, the number of multiplications for all eleven types of the m-D discrete orthogonal transforms needed by the proposed algorithm are only 1/m times that of the commonly used corresponding row-column methods, and for complex input, it is further reduced to 1/(2m) times. The number of additions required is also reduced considerably. Furthermore, the proposed algorithm has a simple computational structure and is also easy to be im-plemented on computer, and th     

On basic properties of fault-tolerant multi-topology routing

Multi-topology routing has recently gained popularity as a simple yet efficient traffic engineering concept. Its basic purpose is to separate different classes of network traffic, which are then transported over disjoint logical topologies. Multi-topology routing is used as a basis for implementation of an IP fast reroute scheme called Multiple Routing Configurations (MRC).MRC has a range of attractive properties, but they do come at a cost. In order to guarantee recovery from any single link or node failure in the network, MRC has to maintain several logical topologies and thus an increased amount of routing information. The number of the logical topologies in MRC need not be large; even simple heuristic algorithms often yield good results in practice. However, why this is the case is not fully understood yet.In this paper, we introduce a theoretical framework for fault-tolerant multi-topology routing (FT-MTR). MRC is a practical implementation of FT-MTR in connectionless IP networks. We use FT-MTR to study how the internal topological structure of the communication network relates to two important problems. The first problem is minimizing the number of logical topologies and thus the routing state in FT-MTR. We show how to use the sets of nodes that separate the topology graph to devise an advanced heuristic for “intelligent” construction of the logical topologies. Finding the separating sets in a topology graph is computationally demanding; we present an algorithm that performs well in tested real network topologies. We evaluate the separation-set based heuristic for the logical topology construction and show that it outperforms the known MRC heuristics.The second problem is the FT-MTR load distribution after a failure. We use the separating sets to devise a novel algorithm for failure load distribution. This algorithm does not require knowledge of the traffic demand matrix, still, our tests indicate that it performs as good as, or better than, known MRC load-distribution algorithms that do require the demand matrix as input.     

Single-Iteration Training Algorithm for Multi-Layer Feed-Forward Neural Networks

A new methodology for neural learning is presented. Only a single iteration is needed to train a feed-forward network with near-optimal results. This is achieved by introducing a key modification to the conventional multi-layer architecture. A virtual input layer is implemented, which is connected to the nominal input layer by a special nonlinear transfer function, and to the first hidden layer by regular (linear) synapses. A sequence of alternating direction singular value decompositions is then used to determine precisely the inter-layer synaptic weights. This computational paradigm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information transfer within a neural network. Examples show that the trained neural networks generalize well.     

Cyclic reduction algorithm for solving collocation systems

In this paper, we present cyclic reducation and FARC algorithms for solving spline collocation system. The costs of these algorithms are 0(N ²logN) and O(N ²log logN) respectively, for an N x N grid.     

梯度法求解弹道导弹扰动引力的并行方法研究

根据远程弹道导弹在发射过程中对外部空间扰动引力场信息的需求,运用梯度法对外部空间扰动引力进行研究,为克服远程弹道导弹扰动引力计算模型复杂、计算量大、不容易在弹上计算机上实时计算的缺点,利用3台计算机组成主从模式并行计算模型,快速解算外部空间扰动引力。实验结果表明,该并行方法可以满足弹载计算机快速计算的要求,并能达到较高的精度。