大型自动埋弧焊成套设备的研究

本文介绍了一种结构新颖的埋弧焊成套设备,并就埋弧焊成套设备中的一些主要部件作了分析说明。该设备采用的平移式横梁结构、三点式九滚轮导轨装置以及焊缝自动跟踪装置,对满足同平面内多道长焊缝的焊接有独到之处。     

Flow patterns in granulating systems

Particle flow patterns were investigated for wet granulation and dry powder mixing in ploughshare mixers using Positron Emission Particle Tracking (PEPT). In a 4-l mixer, calcium carbonate with mean size 45 μm was granulated using a 50 wt.% solution of glycerol and water as binding fluid, and particle movement was followed using a 600-μm calcium hydroxy-phosphate tracer particle. In a 20-l mixer, dry powder flow was studied using a 600-μm resin bead tracer particle to simulate the bulk polypropylene powder with mean size 600 μm. Important differences were seen between particle flow patterns for wet and dry systems. Particle speed relative to blade speed was lower in the wet system than in the dry system, with the ratios of average particle speed to blade tip speed for all experiments in the range 0.01–0.25. In the axial plane, the same particle motion was observed around each blade; this provides a significant advance for modelling flow in ploughshare mixers. For the future, a detailed understanding of the local velocity, acceleration and density variations around a plough blade will reveal the effects of flow patterns in granulating systems on the resultant distribution of granular product attributes such as size, density and strength.     

Introducing robustness in model predictive control with multiple modelsand switching

Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples.     

焊缝跟踪和物料跟踪

介绍宝钢 1 5 5 0热镀锌机组焊缝跟踪和物料跟踪控制系统的配置和功能 ,以及系统应用软件的功能和现场使用情况。     

Adaptive Motion/Force Tracking Control for a Class of Mobile Manipulators

In this paper, modeling and adaptive motion/force tracking control is considered for a class of mobile manipulators under the holonomic and affine constraints with the presence of uncertainties and disturbances. Based on a suitable reduced dynamic model, adaptive controllers are proposed to ensure that the states of a closed‐loop system asymptotically track desired trajectories while the constraint force remains bounded by tuning design parameters. Detailed simulation results confirm the effectiveness of the control strategy.     

二进制无线传感器网络目标跟踪问题的研究

无线传感器网络是近几年发展起来的一门新技术,其研究的重点之一是目标跟踪问题。二进制传感器网络由于其低廉的布设代价、体积小、低能耗以及传感器节点简单,正得到越来越多的关注并用于目标跟踪。目前二进制无线传感器网络中的目标跟踪方法主要分为两大类:基于分段线性拟合的方法和基于粒子滤波的方法。现分别归纳总结现有二进制无线传感器网络中目标跟踪的两大类方法的研究成果并指出其优缺点以及未来的研究方向或需要完善的工作。     

论软件项目风险管理

风险管理一直是软件项目管理中的重点和难点问题。对风险的定性/定量分析、制定风险应对策略、风险跟踪与监控进行了深入的研究,对项目管理过程中的风险问题做了全面的阐述。     

机器人系统全局渐近稳定非线性PD+轨迹跟踪控制

采用一类具有“小误差放大、大误差饱和”功能的非线性饱和函数来改进常用的线性比例微分加（ＰＤ＋）机器人系统动力学控制,以形成非线性ＰＤ＋（ＮＰＤ＋）控制,从而获得更快的响应速度和轨迹跟踪精度．应用Ｌｙａｐｕｎｏｖ直接稳定性理论和ＬａＳａｌｌｅ不变性原理证明了闭环系统的全局渐近稳定性．两自由度机器人系统数值仿真结果表明了所提出的ＮＰＤ＋控制具有良好的控制品质．     

基于跟踪微分器的离散滑模控制器

利用跟踪微分器设计了一种新的离散滑模控制器,可以从不连续的指令信号中合理提取连续信号及微分信号,且不需要利用线性外推的方法预测指令信号下一时刻的值及其微分．与基于趋近律的离散滑模控制器进行的对比仿真表明,所设计的控制器在保持传统滑模控制固有强鲁棒性的同时,控制器的输出几乎不存在抖振现象,而且在跟踪不连续的指令信号时,系统表现出良好的动态品质．     

Human tracking and silhouette extraction for human–robot interaction systems

In this study, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with a pan-tilt stereo camera, so that it can assist in gesture and gait recognition in the field of Human–Robot Interaction (HRI). The proposed system consists of three modules: detection, tracking and silhouette extraction. These modules are robust to camera movements, and they work interactively in near real-time. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift-based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap was estimated in advance and then effectively incorporated into the graph-cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data, and it was shown to detect and track multiple people very well and also produce high-quality silhouettes.