An Intelligent Robust Tracking Control for a Class of Electrically Driven Mobile Robots

This paper addresses the problem of designing robust tracking control for a class of uncertain wheeled mobile robots actuated by brushed direct current motors. This class of electrically‐driven mechanical systems consists of the robot kinematics, the robot dynamics, and the wheel actuator dynamics. Via the backstepping technique, an intelligent robust tracking control scheme that integrates a kinematic controller and an adaptive neural network‐based (or fuzzy‐based) controller is developed such that all of the states and signals of the closed‐loop system are bounded and the tracking error can be made as small as possible. Two adaptive approximation systems are constructed to learn the behaviors of unknown mechanical and electrical dynamics. The effects of both the approximation errors and the unmodeled time‐varying perturbations in the input and virtual‐input weighting matrices are counteracted by suitably tuning the control gains. Consequently, the robust control scheme developed here can be employed to handle a broader class of electrically‐driven wheeled mobile robots in the presence of high‐degree time‐varying uncertainties. Finally, a simulation example is given to demonstrate the effectiveness of the developed control scheme.     

Group technology based adaptive cell formation using predator-prey genetic algorithm

In recent years, there has been a considerable growth of application of group technology in cellular manufacturing. This has led to investigation of the primary cell formation problem (CFP), both in classical and soft-computing domain. Compared to more well-known and analytical techniques like mathematical programming which have been used rigorously to solve CFPs, heuristic approaches have yet gained the same level of acceptance. In the last decade we have seen some fruitful attempts to use evolutionary techniques like genetic algorithm (GA) and Ant Colony Optimization to find solutions of the CFP. The primary aim of this study is to investigate the applicability of a fine grain variant of the predator-prey GA (PPGA) in CFPs. The algorithm has been adapted to emphasize local selection strategy and to maintain a reasonable balance between prey and predator population, while avoiding premature convergence. The results show that the algorithm is competitive in identifying machine-part clusters from the initial CFP matrix with significantly less number of iterations. The algorithm scaled efficiently for large size problems with competitive performance. Optimal cluster identification is then followed by removal of the bottleneck elements to give a final solution with minimum inter-cluster transition cost. The results give considerable impetus to study similar NP-complete combinatorial problems using fine-grain GAs in future.     

Perceived control over caregiving outcomes: Implications for child abuse.

We predicted low perceived caregiver control over caregiving failure to be related to (a) coercive or abusive parenting and (b) affective reactions to "difficult" children. On the basis of a multidimensional scaling analysis of the Parent Attribution Test (Study 1), we constructed a scale (PCF) that assessed perceived balance of control over caregiving failure (attributed control to caregivers vs attributed control to children). In Study 2, we found low PCF to predict abusiveness and nonabusive coerciveness among mothers in counseling at a child abuse agency. Additionally, we found low PCF to predict experienced annoyance/irritation among unrelated mothers interacting with children at relatively high risk for abuse (compared with their lower-risk siblings). We interpreted results as demonstrating the potential importance of low perceived control as a moderator of negative affect in response to difficult children. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A refined evaluation of the gas-phase water-dimerization equilibrium constant within non-rigid BJH- and MCY-type potentials

The flexible BJH- and flexible or semiflexible MCY-type water-water potentials (4 potential modifications in each nonrigid family, i.e., altogether 12 potentials) are used for evaluation of the gas-phase water-dimerization equilibrium constants. The potential-energy term is adjusted for best reproduction of the available experimental equilibrium constants. An independent test using the experimental steam second-virial coefficient isotopic difference shows that the adjustment also improves the computational evaluation of the difference. A set of dimerization equilibrium constants is suggested over a wide temperature interval (based on the BJH/G, MCY-B, or MCYB potential modifications). The best reproduction of the experimental equilibrium constants (in conjunction with good performance for the second-virial isotopic difference) is produced by the BJH/G potential. The results are applicable to various problems such as the formation of water clusters in large-scale natural and artificial water jets (e.g., hydrogen-oxygen rocket motors, orbital capsule water dumps, water ejection from a comet nucleus) or in atmospheric chemistry.     

HTML5在移动互联网中的应用

随着移动通信技术的革新及互联网产业的迅猛发展,以移动互联网为代表的移动数据业务呈现出快速增长的势头,HTML5的出现给移动互联网带来了新的变革。本文首先介绍了移动互联网的发展现状、业务模式,HTML5的发展与技术特点,然后对HTML5在移动互联网中的应用进行了阐述,并列举了部分案例。     

Cell处理器访存特征研究

Cell处理器是一款异构多核处理器,拥有强大的计算能力。但是,在进行应用并行化时,却受到本地存储器容量、访存带宽和数据传输延时等的限制。DMA传输是隐藏长延时、提高存储带宽利用率的有效方法。本文在分析Cell处理器结构基础上,进行了一系列详细的DMA测试,并利用指数拟合技术得到DMA平均带宽模型,发现参与DMA传输的SPE数量和每次DMA传输规模是影响DMA访存带宽的主要因素。     

未知环境下基于约束点的移动机器人路径规划

针对未知环境中障碍物种类多样性和位置不确定性的特点,提出了基于约束点的路径规划方法。首先对机器人在未知环境中检测到的局部障碍物信息进行分类和几何特征属性描述,得其约束点信息,然后引入改进后的A*算法,将其搜索范围局限于约束点上,计算约束点的评价函数值后得到子目标点,机器人到达子目标点后,若陷入死区,则采取回溯路径策略,重新选择子目标点,否则根据该点所属的障碍物种类采取跨越或绕行避障策略,最后移动机器人在未知环境中顺利到达目标点。仿真研究说明本文提出的路径规划方法具有可行性和有效性。     

基于组播源移动的组播树修改过程研究

特定源组播(SSM)是现在应用最广泛的组播模型。随着无线网络的快速发展,移动用户不断增加,移动环境为越来越多的用户提供有限的、共享的带宽,这样的现实更加重了网络对组播服务的需要。然而,特定源组播(SSM)对组播源移动的支持仍然是一个有待解决的问题。本文将针对组播树修改协议(TM)进行分析和改进,进一步完善组播树修改协议过程。     

NDN数据提供者移动支持策略能耗建模与分析

基于数据提供者的移动节点在网络中的不同位置及不同移动速度,结合命名数据网络（NDN）请求者驱动的数据传输模式,提出了3类NDN移动支持策略的网络能耗解析表达式,为NDN移动网络的研究提供了形式化的建模方法.对这3类移动支持策略在不同场景下能耗的分析与比较结果表明,数据流行度分布、移动节点所处位置及移动速度对策略的能耗影响不尽相同,为后续探求最优能效的移动支持策略提供了理论参考.     

一种引入通信的多移动机器人编队方法*

提出以视觉跟踪为基础并引入通信进行多机器人的编队控制方法,根据需要编写了一种新的通信协议,采用闭环l-Φ实现编队算法.这种多机器人编队控制避免了视觉系统的局限,能够更好地在复杂未知环境中协作完成任务,解决了编队控制的无反馈和实时性不高的问题,使得机器人能够准确迅速地进行跟踪和通信编队,一起顺利达到目标点.试验结果证明了该方法的有效性.