直升机模拟器操纵负荷系统建模与试验研究

为提高某型直升机飞行模拟器操纵系统操纵力感逼真度,将直升机操纵系统分布参数分段集中化处理,利用最小二乘参数估计法得到其线性模型,并以纵向通道为例建立了杆力-位移模型和电动力伺服加载系统模型。将模型应用于某型直升机飞行模拟器并进行力感试验,试验结果表明,所建立的杆力-位移模型与实装飞机力感特性相吻合,充分证明了杆力-位移模型的有效性,该模型已成功地应用于某型直升机飞行模拟器操纵负荷系统。     

Research on social relations cognitive model of mobile nodes in Internet of Things

Interaction and communication between humans with smart mobile devices are a new trend of development in Internet of Things (IoT). With the powerful sensing capability of smart device and human mobility, various services could be provided by building a trusted chain between service requesters and suppliers. The cognition of social relations between mobile nodes is the basis of final mobile-aware services. It involves many decision factors, such as time, space and activity patterns. Using social network theory, a new cognitive model for social relations of mobile nodes in IoT is proposed. Firstly, nodes' social relations are reasoned and quantified from multiple perspectives based on the summary of social characteristics of mobile nodes and the definition of different decision factors. Then the location factor, interconnection factor, service evaluation factor and feedback aggregation factor are defined to solve the shortcomings in existing quantitative models. Finally, the weight distribution is set up by information entropy and rough set theory for these decision factors; it can overcome the shortage of traditional methods, in which the weight is set up by subjective ways and hence their dynamic adaptability is poor. We compare our cognitive model to existing models using MIT dataset by defining a variety of test indicators, such as network overall density (NOD), the degree center potential (DCP), the network distribution index (EI), etc. Simulation results show that, the cognitive model has better internal structure and significant validity in network analysis, and thus can provide mobile-aware service effectively in dynamic environment.     

A review of visual inertial odometry from filtering and optimisation perspectives

Visual inertial odometry (VIO) is a technique to estimate the change of a mobile platform in position and orientation overtime using the measurements from on-board cameras and IMU sensor. Recently, VIO attracts significant attentions from large number of researchers and is gaining the popularity in various potential applications due to the miniaturisation in size and low cost in price of two sensing modularities. However, it is very challenging in both of technical development and engineering implementation when accuracy, real-time performance, robustness and operation scale are taken into consideration. This survey is to report the state of the art VIO techniques from the perspectives of filtering and optimisation-based approaches, which are two dominated approaches adopted in the research area. To do so, various representations of 3D rigid motion body are illustrated. Then filtering-based approaches are reviewed, and followed by optimisation-based approaches. The links between these two approaches will be clarified via a framework of the Bayesian Maximum A Posterior. Other features, such as observability and self calibration, will be discussed.     

Parallel particle filter for tracking road centrelines from high-resolution SAR images using detected road junctions as initial seed points

Acquiring road junction information is helpful for improving the quality of road network extraction. This article presents a new road network extraction method with three stages. First, road junction candidates are extracted by our previously proposed valley-finding algorithm. Second, numerous particle filters running in parallel track road centrelines starting from all of the detected junction candidates. Finally, the road centrelines are approximated by fitting the tracked centrepoints. The main contribution of this article lies in two aspects. First, road centrepoint tracking routes are launched simultaneously by considering the detected road junctions as starting points, which helps overcome the interference of various obstacles. Second, parallel tracking is implemented by a graphics processing unit (GPU) running accelerated particle filters, which significantly improves the execution time of the road network extraction task. The experimental results show that our proposed method not only handles various obstacles that occur on the roads capably, but also, on average, is 10.5 times as fast as previous methods. We compared the proposed method with two other existing methods in the literature using two different synthetic aperture radar (SAR) images to validate the superior performance of our proposed method.     

物料计量系统鲁棒控制器设计

通过传送带速度调节给料系统 ,分析了包装机械连续喂料称重计量系统的性能 ,给出了一种提高系统鲁棒性的控制器设计方法 ,并根据该给出的H∞ 方法 (即极小化极大法 )设计了一个鲁棒控制器加于原系统 ,使原系统的性能得以提高     

基于LTE的BBU集中化组网分析

BBU集中化组网能够有效地提高无线网络资源利用率,加快网络建设速度,降低运营成本,动态地解决无线业务迁移问题。通过分析BBU基带池集中化的技术及其特性,结合网络建设实际应用,提出BBU集中化组网建议。     

属性权重未知情形下的q阶orthopair犹豫模糊TOPSIS法

在多属性决策问题中,q阶orthopair犹豫模糊集可以有效地处理不确定信息.基于Theil不等系数,提出一种新的q阶orthopair犹豫模糊距离测度,并研究该距离测度的性质.针对属性权重完全未知的q阶orthopair犹豫模糊多属性决策问题,构建离差最大化的属性权重模型.基于该权重确定模型和q阶orthopair犹...     

大型全回转浮式起重机平衡系统优化数学模型

针对大型全回转浮式起重机的结构和工况特点,在满足抗倾覆稳定性要求下,将浮式起重机自重产生的不平衡力矩与起升货物产生的不平衡力矩之和的均方根力矩作为目标函数值,建立以平衡系统主要构件强度、刚度、结构尺寸和回转轮压合理性为约束条件的多目标设计优化数学模型,运用遗传算法优化浮式起重机平衡系统,最终得出优化数据.该数学模型在具体优化过程中取得较为满意的优化结果,为大型全回转浮式起重机的设计优化提供有效方法.     

配网自动化交换机研制

从配网自动化网络传输报文的特点出发,对交换机的传输带宽、存储转发延时、强电磁干扰下的零丢包、环网自愈时间、网络安全控制、流量分类控制、机箱结构等方面进行需求分析,提出了一种适用于配网自动化网络的交换机研制方案。