基于蚁群算法的固体火箭发动机总体参数优化

为建立一种支持连续域、离散域混合变量的优化算法以用于固体火箭发动机总体参数优化,改进了基本蚁群算法,融入"网格划分"、"哑元化"和"变尺度局部搜索"三种策略,以改进算法的寻优性能和使用范围,其中局部搜索算法仍采用蚁群算法。使用了几个较具欺骗性的经典测试函数对改进蚁群算法进行了测试,计算结果表明改进蚁群算法找到全局最优值的概率较大。应用改进蚁群算法对固体火箭发动机总体设计中的两个重要总体参数——燃烧室工作压强和喷管面积比,进行了优化求解,获得了满意结果。诸算例的优化结果表明,该改进蚁群算法具有支持混合变量,全局寻优性能稳定和搜索精度高的优点,对工程优化设计问题具有较好的寻优性能和更强的适用性。     

面向维修性设计的民机产品拆卸序列规划方法

维修拆卸序列规划是产品维修性设计的重要内容。深入研究了面向维修性设计的产品拆卸建模方法,将民机产品分为部件模块与联接件两部分,构建了部件联接图模型,通过关联矩阵描述了部件模块与联接件的相互关系。分两步给出了民机产品拆卸序列规划方法:利用干涉矩阵确定部件模块的可行拆卸方向,以拆卸代价最小为目标,提出了基于有序搜索的民机产品部件模块的拆卸序列规划算法;考虑联接件的拆卸顺序,以拆卸工具更换次数最小为目标,提出了基于基因成对交叉与变异的遗传算法的完整拆卸序列优化方法。最后,结合某飞机前起落架系统给出了应用实例,阐明了本文方法的有效性。     

基于北斗导航检测平台的时间量值传递系统研究

研究了基于北斗卫星的北京市导航检测平台的时间量值传递系统,它以卫星共视法作为数据比对的条件,采用修正值预估技术和相位补偿技术来提高铷钟的准确度与稳定度。本系统可实时地将地方原子时标与UTC（NIM）进行比对溯源,实现北斗卫星导航检测平台的时间量值可靠传递,保证地方原子时标与国家时间基准UTC（NIM）同步差在±10ns以内,以满足北斗导航产品研制、开发和应用的需要。     

自适应预测补偿的迭代制导方法及其应用研究

针对迭代制导完成后入轨参数或终端程序角修正问题,研究一种基于模型参考的自适应预测补偿迭代制导算法在运载火箭上的应用。该算法在经典迭代制导算法的基础上,根据预测的迭代终端程序角和飞行视加速度的参考模型,对关机点参数进行补偿,依据补偿后的终端指标重新规划飞行轨迹,进而得出满足入轨参数或终端程序角偏差修正的制导指令,提升迭代制导对入轨参数偏差或终端程序角的修正能力。此外,阐述了经典迭代制导的基本算法,概括了自适应预测补偿迭代制导算法的基本原理,并以大推力直接入轨、终端程序角大偏差以及满足终端程序角约束为例,给出相应工况的自适应预测补偿的迭代制导算法。仿真结果表明：该算法对入轨参数和终端程序角偏差具有一定的修正能力。     

Pareto遗传算法在气动外形优化中的应用

Pareto方法作为一种多目标优化方法,能够一次性获得优化问题对应的不同权重分配情况下的所有最优解集。它与遗传算法结合产生的Pareto遗传算法,是求解多目标优化问题的Pareto最优解集合的一种有效手段。本文将两种常用的Pareto遗传算法,MOGA方法和两支联赛遗传算法应用到气动外形优化中,针对具体算例进行气动外形的优化设计,得到了满意的优化设计结果。     

基于遗传算法与DSM的产品结构分解聚类方法

产品结构的分解聚类在产品开发中有着重要的地位,在用设计结构矩阵(D es ign structure m atrix,DSM)对产品结构进行建模的基础上,通过遗传算法实现了产品结构分解聚类的智能化和分解聚类结果的最优化。在算法的设计过程中开发了一种对DSM进行二维编码的方法,并给出了在二维编码基础上的多点杂交和基本变异方法。在构造适应度函数时,综合考虑了DSM模型中各元素之间的联系、聚类的数目以及各聚类中元素的数目。最后以某摩托车发动机为例,用该算法实现了产品结构DSM模型的智能化分解聚类,验证了该算法的可行性。     

An unsupervised classification method of flight states for hypersonic targets based on hyperspectral features

In response to the challenges of aerospace defense caused by the rapid development of hypersonic targets in recent years, the research on the unsupervised classification of flight states for hypersonic targets is carried out in this paper, which is based on the Hyperspectral Features (HFs) of hypersonic targets covered with plasma sheath during high-speed flight. First, a new concept of the super node is defined to improve classification accuracy by alleviating the intraclass variability of HFs. Then, the frequency domain information of the curve of HFs is utilized to reduce the feature redundancy according to the prior theoretical knowledge that the fluctuation characteristics of HFs of the same flight states are similar. Finally, an unsupervised classification method based on the Density Peak Clustering (DPC) for HFs is designed to class flight states after eliminating the impact of intraclass variability and feature dimension redundancy. The proposal is compared with the traditional classification algorithms on simulated hyperspectral data sets of typical flight states of the hypersonic vehicle and an actual-observation hyperspectral data set. The results indicate that the performance of our proposal has competitive advantages in terms of Overall Accuracy (OA), Average Accuracy (AA) and Kappa coefficient.     

Improving the low orbit satellite tracking ability using nonlinear model predictive controller and Genetic Algorithm

The satellite motion on the reference orbit (RO) with less energy consumption has always persuaded researchers to design optimal control systems. The nonlinear nature and time-varying equations of motion make this quest more challenging. The present study proposes a novel control system for satellite motion on the RO by considering a comprehensive model of its dynamics in orbit and a Nonlinear Model Predictive Controller (NMPC). The NMPC calculates the sub-optimal control inputs of satellite motion reference on the elliptic orbit by minimizing a convex cost function at each stage. Moreover, all weighting parameters of the cost function are optimized by the Genetic Algorithm (GA) to produce less perturbation and guarantee the best NMPC performance. Finally, the implemented NMPC has been compared to a Linear MPC (LMPC). The results show that not only can the NMPC resist against larger errors and perturbations, but it can also compensate for those errors by returning the satellite to its main orbit and maintaining it.