小型无人机翼型优化设计

采用类别形状函数变换（CST）方法对翼型参数化描述;利用Fluent软件,进行翼型升力系数和阻力系数的气动计算;以升阻比最大为优化目标,通过拉丁超立方设计生成样本点,建立了径向基神经网络（RBF）代理模型;使用粒子群优化算法（PSO）,在Isight平台上,实现对Clark Y翼型优化的整个过程。优化翼型升阻比比原始翼型提高了约10%,表明此种方法是可行的,可用于小型无人机设计的工程中。     

Lunar geophysical parameters inversion based on gravity/topography admittance and particle swarm optimization

This paper presents a FORTRAN computer program. The program as code will be used for lunar parameter inversions based on gravity/topography admittance. This will be done by assuming that the lunar lithosphere is modeled as a thin elastic spherical shell. The parameters discussed here include; load ratio, crustal thickness, subsurface load depth, crustal density and elastic lithosphere thickness. The admittance of the best-fitting model can be found through automatically adjusting misfits between one theoretical admittance and an observed one. The results in this paper indicate that this research’s theoretical model is reasonable for exploring the best-fitting parameters. In addition, this code is not only able to automatically and simultaneously calculate the global optimum solution of the parameters studied, but also performs well in computational speed. The code can be easily modified to include more parameter inversions; such as the inversion for subsurface density anomaly and the case of considering infilling material in some lunar mare basins.     

Optimal mission planning of the reconfiguration process of satellite constellations through orbital maneuvers: A novel technical framework

In this paper, a general new methodology is presented for the orbital reconfiguration of satellite constellations on the basis of Lambert targeting theorem. In view of the cost and risk reduction, it is very important to consider the problem of satellite constellation reconfiguration with the two constraints of overall mission cost minimization and the desired final configuration. Hence, the dependent non-simultaneous deployment approach is proposed to minimize overall fuel cost. Despite the fact that the satellites deploy in a non-simultaneous manner, supplementary phasing maneuvers on the target orbital pattern to achieve the desired orbital configuration are avoided. Moreover, a novel idea is presented to optimize the flight of satellites, which plays an important role in complying with the constraint of overall fuel cost minimization as much as possible. In order to achieve the global optimal solution of the satellite constellation reconfiguration problem, the efficient hybrid Particle Swarm Optimization/Genetic Algorithm (PSO/GA) technique, is implemented. Finally, to indicate the superiority of the presented method, a comparison to the simultaneous maneuver viewpoint is made on a number of representative cases. The obtained results imply significant reduction of reconfiguration costs by employing the proposed method.     

基于新体制的单基线定位技术研究

结合工程应用,研究单基线利用模糊相位差对地面固定目标的高精度快速定位方案与关键技术,分析自适应随机惯性权值粒子群算法的性能。仿真结果表明,通过优化和改进,基于新体制的该算法能获得较好的定位性能。     

基于粒子群优化算法的飞机维修计划编制优化

针对国内航空公司的维修生产管理,分析了维修计划的编制流程,建立了相应的整数规划数学模型,该模型采用维修停场损失、维修加班费用和维修外包费用的和作为目标函数,可用于混合机型机队的定检维修计划的制定。同时分析研究了粒子群优化算法,并采用该算法对模型进行求解。数据仿真结果表明,建立的模型和求解算法切实可行。     

吸收变异的粒子群算法及应用

提出了一种改进的粒子群算法,称为ConvergencemutationPSO(CM_PSO)。该算法根据粒子群中各粒子的适应值动态地调整粒子数量,把部分适应度差的粒子适当汇聚到适应度好的区域,在不损失全局搜索能力的同时,增强局部搜索能力。在将该算法应用于雷达组网误差配准问题中,提出了一种基于CM_PSO的误差配准技术。仿真表明,该算法能有效配准,与对比方法相比较,具有更好的收敛精度和更快的进化速度。     

立方星电源系统最大功率点跟踪优化控制方法

针对立方星在能量来源严重受限条件下如何提高太阳能利用率的难题,提出一种适用于立方星的集中供电式空间微电源架构(EPS),并设计基于改进粒子群优化算法的最大功率点跟踪(MPPT)控制策略来提升能量转换效率。首先,推导太阳电池阵列的数学模型,并根据太阳电池阵列的工作特性,提出电源系统最大功率点跟踪控制的物理系统实现结构。其次,设计基于改进粒子群优化(PSO)的最大功率点跟踪控制算法,并进行了数学仿真校验。最后,对所设计的电源系统架构进行了硬件实现和试验验证。地面试验结果表明,电源系统的太阳能最大转换效率可达95.5%。该电源系统成功应用于世界首颗12U立方星“翱翔之星”的飞行试验,在轨数据表明电源系统工作状态良好,为微纳卫星电源系统的设计提供了有益参考。     

基于粒子群优化算法的永磁电机热网络参数识别

监测永磁电机的永磁体温度对于保证电机的使用寿命至关重要,因为过高的温度会产生永磁体不可逆失磁现象。提出了一种基于粒子群优化算法的永磁电机热网络参数识别方法,实现用热网络监测永磁体的温度。该方法首先建立永磁电机的热网络模型,利用粒子群优化算法结合电机温升试验所得温度数据对热网络模型的主要热力参数进行识别;然后利用该热网络模型进行在线温度识别,识别过程能够快速收敛,具备良好的辨识精度;最后,通过对比仿真识别温度和电机温升试验数据,验证了该方法的准确性。     

一种高稳定度帆板驱动系统的摩擦参数辨识

为了减少帆板驱动机构（SADA）对太阳帆板的激励作用和降低摩擦的影响,以永磁同步电机作为驱动源,提出了一种基于LuGre模型的摩擦参数辨识和补偿方法.为了能够准确的进行摩擦参数的试验辨识,设计了SADA系统摩擦力矩测试平台两者相结合进行了试验辨识,并将试验辨识所得到的摩擦模型参数代入SADA驱动系统模型中.通过仿真和试验表明：试验辨识较准确,且摩擦补偿后的SADA系统消除了正弦跟踪中速度过零时的波形畸变现象,能够有效改善SADA系统的动态性能     

考虑柔性检修计划的圆钢热轧批量调度

针对考虑柔性检修计划的圆钢热轧批量调度问题,构建了以最小化最大完工时间、订单提前及拖期总时长为目标函数的整数规划模型,用以制定有效的机器检修与批量生产协作计划。结合模型特征,提出一种改进多目标粒子群算法(IMPSO)实现求解。算法采用基于混沌加权适应度计算的插入式方法生成初始粒子群体;根据问题约束特征,设计修复规则对群体进化过程中产生的不可行粒子进行修复;采用精英策略保留算法迭代过程中的优势个体,并根据精英集合为每个粒子选择更新所需的极值;针对问题变量的离散特征,引入基于遗传操作的粒子更新方式。实验结果表明,模型和算法是可行和有效的。