基于遗传算法的多部测速雷达布站优化研究

通过部署于不同地点的多部无源多普勒测速雷达,可以对有辐射信号源的机动飞行目标进行跟踪测量,并且可以对目标位置和速度信息进行最佳估计。本文探讨了遗传算法在测速雷达布站优化中的使用方法,分析了误差传播矩阵,建立了简易目标函数,利用遗传算法对信标体制下的多普勒测速单站的布站几何进行了优化。     

Wing optimization of propeller aircraft based on actuator disc method

Propeller aircraft are widely used in general aviation. The rotating propeller has a strong effect on the aerodynamic performance of the wing. This paper uses an actuator disc to model the effect of the propeller. A wing optimization method is developed with the actuator disc method. Several wing optimizations with different slipstream settings are studied. The twist angle and airfoils of the wing are used as the design variables. The results show that the propeller slipstream and slipstream directions have a strong influence on the optimization process. Powered-on optimization with a slipstream can obtain better drag reduction results than unpowered optimization. The drag decomposition results show that most of the drag reduction comes from the form drag reduction. The symmetric “inboard-up” slipstream configuration is found to have the highest lift-to-drag ratios, which are 18.87 for the twist angle optimization and 19.15 for the airfoil optimization.     

基于自适应神经模糊推理算法的无人机电推进燃料电池供气系统性能优化

本文针对某无人机基于聚合物交换膜燃料电池和锂离子电池的混合动力电推进系统的应用,研究开发了一种基于自适应神经模糊推理系统的电源管理系统控制技术,以控制混合动力电力推进系统,同时优化燃料电池供气系统的性能。本文以所建立的某无人机混合电推进系统数学模型为研究对象,研究了燃料电池电流与燃料电池供气系统压缩机功率之间的关系,建立了燃料电池电流与最佳压缩机功率关系的参考模型。在参考模型的基础上,引入自适应控制器来优化燃料电池供气系统的性能。基于自适应神经模糊推理系统的控制器将压缩机的实际运行功率动态调整到参考模型中定义的最佳值。自适应控制器的在线学习和训练能力用来辨识燃料电池电流的非线性变化,并产生压缩机电机电压的控制信号,以优化燃料电池供气系统的性能。在Matlab 仿真环境中开发了质子交换膜燃料电池和锂离子混合动力电推进系统模型并对所设计的控制器进行了仿真分析,结果表明基于自适应神经模糊推理系统的控制器为燃料电池供气系统压缩机性能优化提供了一种新颖而全面的途径,使燃料电池供气系统获得最大净功率输出。将燃料电池系统的净功率输出与最佳压缩机功率和恒定压缩机功率进行了比较,结果表明优化的压缩机功率配置比恒定的压缩机功率配置节能2.62%。同时,燃料电池自适应神经模糊推理系统控制器优化了燃料电池供气系统的能量利用。     

An optimization model of parameter matching for aircraft catapult launch

To efficiently and fully utilize aircraft carrier resources, an optimization model is presented to deal with parameter matching between aircraft and carrier in the process of aircraft catapult launch. Based on carrier aircraft longitudinal dynamic equations and theorem of kinetic energy in catapult launch course, the work characteristics of different forces are learned and a theory model of parameter matching is deduced. In view of the uncertainty of the model parameters of the theory model and the low matching accuracy of the approximate model, an optimization model of parameter matching is introduced in line with the structure of theory model and the approximate model and is generated by the proposed immune genetic algorithm. Compared with the original genetic algorithm and immune algorithm, the proposed algorithm has better calculation accuracy and convergence. The calculation results show that the optimization model occupies certain application value of engineering estimation from the comparison with the relevant literature data and has higher precision than the approximate models. The validity of the proposed approach is verified with numerical case study on a carrier based aircraft.     

Multi-disciplinary design optimization with fuzzy uncertainties and its application in hybrid rocket motor powered launch vehicle

In this paper, an Uncertainty-based Multi-disciplinary Design Optimization (UMDO) method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket Motor (HRM) powered Launch Vehicle (LV). In the method proposed, membership functions are used to represent the uncertain factors, the fuzzy statistical experiment is introduced to analyze the propagation of uncertainties, and means, standard deviations and credibility measures are used to delineate uncertain responses. A geometric programming problem is solved to verify the feasibility of the Fuzzy-based Multi-Discipline Feasible (F-MDF) method. A multi-disciplinary analysis of a three-stage HRM powered LV involving the disciplines of propulsion, structure, aerodynamics and trajectory is implemented, and the mathematical models corresponding to the F-MDF method and the MDF method are established. A two-phase optimization method is proposed for multi-disciplinary design optimization of the LV, including the orbital capacity optimization phase based on the Ziolkowski formula, and the scheme trajectory verification phase based on the 3-degree-of-freedom point trajectory simulation. The correlation coefficients and the quadratic Response Surface Method (RSM) based on Latin Hypercube Sampling (LHS) are adopted for sensitive analysis of uncertain factors, and the Multi-Island Genetic Algorithm (MIGA) is adopted as the optimization algorithm. The results show that the F-MDF method is applicable in LV conceptual design, and the design with the F-MDF method is more reliable and robust than that with the MDF method.     

智能优化算法及其在飞行器优化设计领域的应用综述

在对国内外相关文献进行系统研究的 基础上,阐述了飞行器优化设计领域应用较为广泛的几种智能优化算法的基本原理,分析了 算法的优缺点和改进方法,总结了算法在飞行器轨迹、气动和控制等学科优化设计中的应用 情况。同时,文章对在飞行器优化设计领域应用刚刚起步,但较有发展前景的智能优化算法的 特点和应用情况进行了概述。最后,对智能优化算法在飞行器优化设计领域应用的未来研究 方向进行了分析。
     

相控阵雷达搜索方式下波位编排与优化

分析不同波位编排方式对相控阵雷达能量需求与搜索性能的影响,给出了搜索方式下较为优化的波位编排方式。然后在分析相控阵雷达波束展宽效应的基础上,提出了非均匀划分扫描空域并对波束展宽效应进行补偿的方法,对波位编排方式进一步优化。最后利用该方法仿真分析了波束宽度与天线增益的变化,结果表明可有效补偿波束展宽效应带来的影响。     

箭载GPS信号传播误差改正模型的选优

误差修正模型是影响箭载GPS定位精度的关键问题之一。针对几种常用的GPS信号传播误差改正模型,探讨了各模型伪距延迟修正量的计算方法,分析和比较了各模型之间的差异,给出了组合误差修正模型的选优标准。实测数据计算结果表明,选优后的误差修正模型可有效提高目标定位精度。     

机载导弹电路故障诊断优化方法探讨

针对机载导弹电路故障诊断问题 ,提出了在赋模糊权的二部图中求解故障诊断费用最小的诊断顺序的数学模型 ,并给出了该模型的优化算法。根据算法可方便地得出故障诊断顺序的优化决策方案 ,使机载导弹电路故障诊断更为经济和快捷有效     

基于特征的航空钣金零件快速设计方法研究与应用

在航空钣金零件设计知识没有得到管理和应用的情形下,钣金零件设计需要查询大量的纸质文件,导致建模时间长,重复劳动多,设计效率低下,容易产生人因错误.由于设计人员水平和习惯差异,航空钣金零件建模过程和方法不统一,模型质量参差不齐,难以实现规范化建模和最优化设计,也给后续工艺设计及加工制造带来不便.本文使用CATIA二次开发技术、基于知识工程的设计技术和CATIA航空钣金设计模块接口配置技术等,在总结提炼钣金特征设计知识、建立标准规范库和特征模板库的基础上,构建了基于特征的航空钣金零件快速设计系统,实现了航空钣金零件的快速规范化建模和最优化设计.系统已在型号研制中得到验证和使用,效果明显,大大提高了航空钣金零件的设计效率和质量.