基于CSI的区域粒子化的室内定位算法的研究

在实际的室内环境下,Wi-Fi信号会受到复杂环境下物体的影响而降低室内定位精度,为此,提出基于CSI的区域粒子化的室内定位算法。区域粒子化的主要思想是将计算得到的定位区域不断进行划分,减小定位区域面积,然后通过余弦相似度算法获取位置坐标。由于信号状态信息CSI在复杂环境下更加稳定,而且定位区域面积通过粒子化的过程不断缩小,得到的位置坐标也更加接近于实际的位置坐标,最后通过实验对算法进行验证得到更高的定位精度。

双目标区域化PSO热风炉均压滑模控制

目的针对热风炉冷风均压控制中存在的大惯性、大滞后和超调量大等问题,提出一种基于双目标区域化粒子群算法的热风炉冷风均压滑模控制策略。方法所提策略将冷风流量作为控制量,将冷风压力设为被控量,将滑模控制算法与粒子群优化算法相结合,选取常规滑模算法并对其进行改进,运用指数趋近律降低外部扰动对系统产生的影响,并加入双目标区域化粒子群算法对滑模切换增益系数和指数趋近系数进行寻优,通过粒子平均排名、环境检验参数等指标作为寻优条件,以求取最优滑模控制律对冷风压力进行调控,进而实现均压优化控制效果。结果仿真结果表明:所设计控制策略在适配条件下于58.2 s时达到稳定,超调量为4.1%,在失配且加入干扰条件下于72.4 s时达到稳定,超调量仅为17.6%,与串级PID控制和常规滑模控制相比,策略拥有良好的超调和快速达到稳定的能力。结论工程应用表明:冷风压力波动偏差仅为±6.48 Kpa,所提控制策略拥有稳定性高、响应快和超调量小的特点,能够较好应用于实际生产中热风炉冷风均压工况要求。

基于增强的物质点法的非均质弹性材料仿真方法研究

在基于物理的仿真领域,近几年流行的物质点法已经成为一种越来越重要的仿真方法.物质点法已经可以仿真雪、物质状态变化、颗粒状的沙子以及粘弹性的泡沫等物理现象.现有的各种复杂物理现象的模拟已经展示了物质点法作为一种通用的求解方法的潜质,然而对于仿真形变体尤其是自然界普遍存在的非均质材质还存在一些不足.当同一网格内部包含多种材质的粒子时,由于背景网格与粒子之间的插值只考虑粒子的几何位置而不包含物质属性信息,导致不同属性的粒子在网格内部表现为"平均化"的运动趋势.为了改进传统物质点法模拟多种材质的缺陷,该文提出了一种模拟非均质弹性材料的仿真方法.首先,在预处理过程中将仿真物体离散表示成粒子,针对物质的不同属性粒子的分布,建立物质边界并确定边界粒子,仿真过程中动态更新边界粒子的位置;其次,引入粒子影响域,区分网格内部具有不同属性的粒子,增加网格内部计算自由度;最后,提出一个判断准则,根据物质边界粒子的位置判定仿真粒子是在背景计算网格上求解还是粒子区域上求解.实验结果表明,利用改进的物质点法能够有效地模拟非均质材质弹性体的形变.与有限元法相比,该文方法在模拟非均质弹性体时可以获得相似的效果,并且在模拟拓扑结构变化的问题以及碰撞处理上更有优势.

粒子运动区域和粒子源距离对局部区域聚集生长的影响

以DLA模型为基础,模拟研究了粒子运动区域和粒子源距离的大小对非对称性聚集生长产生的影响。发现粒子随机运动区域和粒子源距离的大小对局部区域聚集生长产生重大的影响。

Multi-path routing algorithm in WSN using an improvedparticle swarm optimization

To slove the problems of constrained energy and unbalanced load of wireless sensor network(WSN)nodes,a multipath load balancing routing algorithm based on neighborhood subspace cooperation is proposed.The algorithm adopts the improved particle swarm optimization(PSO)algorithm,takes the shortest distance and minimum energy consumption as optimization target and divides the nodes in one-hop neighborhood near the base station area into different regions.Furthermore,the algorithm designs a fitness function to find the best node in each region as a relay node and forward the data in parallel through the different paths of the relay nodes.The simulation results show that the proposed algorithm can reduce energy consumption and average end-to-end delay,balance network load and prolong network lifetime effectively.

Robot SLAM with Ad hoc wireless network adapted to search and rescue environments

An innovative multi-robot simultaneous localization and mapping(SLAM)is proposed based on a mobile Ad hoc local wireless sensor network(Ad-WSN).Multiple followed-robots equipped with the wireless link RS232/485module act as mobile nodes,with various on-board sensors,Tp-link wireless local area network cards,and Tp-link wireless routers.The master robot with embedded industrial PC and a complete robot control system autonomously performs the SLAM task by exchanging information with multiple followed-robots by using this self-organizing mobile wireless network.The PC on the remote console can monitor multi-robot SLAM on-site and provide direct motion control of the robots.This mobile Ad-WSN complements an environment devoid of usual GPS signals for the robots performing SLAM task in search and rescue environments.In post-disaster areas,the network is usually absent or variable and the site scene is cluttered with obstacles.To adapt to such harsh situations,the proposed self-organizing mobile Ad-WSN enables robots to complete the SLAM process while improving the performances of object of interest identification and exploration area coverage.The information of localization and mapping can communicate freely among multiple robots and remote PC control center via this mobile Ad-WSN.Therefore,the autonomous master robot runs SLAM algorithms while exchanging information with multiple followed-robots and with the remote PC control center via this local WSN environment.Simulations and experiments validate the improved performances of the exploration area coverage,object marked,and loop closure,which are adapted to search and rescue post-disaster cluttered environments.

A Study of Intermediate Energy Proton-^16O Elastic Scattering Based on the α-Particle Model

In the framework of KMT multiple scattering theory, an optical potential for the intermediate energy proton-160 elastic scattering is presented based on the α particle model of 160. The differential cross sections, the analyzing powers, and the total cross sections of the intermediate energy proton-160 scattering have been calculated by using the obtained optical potential. The main features of the measured angular distributions of the cross section and the analyzing power can be well described. The calculated total cross sections are in good agreement with the experimental data at energies below 0.7 GeV and underestimate the data about 8% at higher energies.

An adaptive smoothed particle hydrodynamics for metal cutting simulation

Normally large amounts of particles are required to accurately simulate the metal cutting process,which consumes a lot of computing time and storage.Adaptive techniques can help decrease the number of particles,hence reducing the runtime.This paper presents a novel adaptive smoothed particle hydrodynamics(SPH)method for the metal cutting simulation.The spatial resolution changes adaptively according to the distance to the tool tip by the particle splitting and merging.More particles are selected in the region where the workpiece and the tool are in contact.Since the contact region constantly changes during the cutting process,two quadrilateral frames are adopted in the adaptive algorithm to dynamically change the distribution of particles.One frame for the refinement,the other for the coarsening.These frames move at the same speed as the tool.To test the computational efficiency,the metal cutting process is simulated by using SPH with three different adaptive approaches.Numerical results show that the proposed adaptive algorithm with dynamic refinement and coarsening can significantly optimize the runtime.