基于改进多目标布谷鸟搜索算法的翼型气动优化设计

布谷鸟搜索（CS）算法是一种新型的受自然现象启发的元启发式智能优化算法，其强大的全局搜索能力和收敛速度受到了广泛关注。多目标布谷鸟搜索（MOCS）算法是一种在单目标布谷鸟算法基础上发展的可以直接求解Pareto解集的多目标优化算法。针对原始MOCS算法的不足，采用一系列措施以提高算法的收敛精度、收敛速度以及解的均匀性：通过引入非支配排序与拥挤距离来改进解的适应度评估；通过改进随机游走策略来提高局部搜索能力；通过引入改进的自适应丢弃概率策略来提高算法的收敛速度；加入档案管理机制，提高解的均匀性。典型的多目标数值算例结果表明，改进的MOCS算法相较于当前主流的NSGA-Ⅱ算法拥有更快的收敛速度和更高的收敛精度。以RAE2822双目标升阻比优化设计为例，将改进的MOCS算法应用于多目标气动优化中，改进的MOCS算法共获得64个Pareto解，优化后的翼型气动性能有明显的提升，设计者可以根据自己的偏好选取不同的Pareto解。对于气动优化问题，改进的MOCS算法与目前主流的NSGA-Ⅱ相比，收敛速度更快。     

基于深度强化学习的智能空战决策与仿真

飞行器空战智能决策是当今世界各军事强国的研究热点。为解决近距空战博弈中无人机的机动决策问题，提出一种基于深度强化学习方法的无人机近距空战格斗自主决策模型。决策模型中，采取并改进了一种综合考虑攻击角度优势、速度优势、高度优势和距离优势的奖励函数，改进后的奖励函数避免了智能体被敌机诱导坠地的问题，同时可以有效引导智能体向最优解收敛。针对强化学习中随机采样带来的收敛速度慢的问题，设计了基于价值的经验池样本优先度排序方法，在保证算法收敛的前提下，显著加快了算法收敛速度。基于人机对抗仿真平台对决策模型进行验证，结果表明智能决策模型能够在近距空战过程中压制专家系统和驾驶员。     

天基光学空间目标监测的初轨确定

针对天基空间目标光学监测时初轨确定（IOD）困难的问题，讨论了计算结果收敛到平凡解的本因，提出了消去平凡解的改进定轨流程。通过构建Laplace初轨确定方法的八次方程，分析了空间目标处于不同相对位置时方程系数和根的性质之间的关系。针对传统Laplace型初轨确定方法收敛到观测平台轨道的现象，给出了平凡解的数学表征和数值验证并提出了消除方法。由于基于Lambert问题利用距离搜索的初轨确定方法进行天基目标监测时对初值相对敏感，利用平凡解消除方法对Gooding法进行了改造，提出了一种适用于天基空间目标初轨确定的方法与流程。最后利用低轨目标监测的实测数据和高轨目标监测的仿真数据对方法进行了验证。结果表明本方法可有效解决平凡解和初值敏感问题，方法具有收敛速度快、精度可靠的特点，且具有普适性，易于理解，便于推广。     

一种基于视觉成像的快速收敛的位姿测量算法及实验研究

 由三维目标与其二维图像估计相对于目标的位置和姿态是计算机视觉成像中的一个重要问题。正交迭代(OI)算法是一种快速、且能全局收敛的姿态估计方法，但是当数据恶化时，不能给出正确的旋转矩阵。本文改进了该算法中旋转矩阵求解方法，避免了旋转矩阵求解中出现的错误。建立了模拟实验系统，使用改进的算法进行测量，在0.45～5.20 m的范围内，摄像机到目标距离的相对误差小于±0.41%；在距离为3 m时，旋转角度测量误差小于±1.8°。数学仿真结果表明，改进后算法的抗噪声能力得到改善，结果更为准确，且能快速收敛。     

一种基于神经网络的飞机载荷参数识别方法

提出一种经遗传算法优化的Kalman滤波神经网络(GA-KFNN)方法,对飞机特定机动下的载荷进行参数识别.首先,构建Kalman滤波神经网络(KFNN),设计了相关改进算法抑制滤波发散,提高了网络的预测精度和抗噪能力;其次,利用遗传算法(GA)优化KFNN的相关参数,使网络能迅速收敛,提高了运算效率.载荷识别结果显示,改进和优化后的GA-KFNN运行稳定,收敛迅速,具有良好的识别精度和泛化能力,满足工程实际需求.     

飞行器气动力参数辨识的一种实用滤波误差方法

提出了一种观测噪声相对于过程噪声较小情况下气动参数识别的实用滤波误差方法，方法不要求已知系统过程噪声和观测噪声方差阵，计算量小，具有一定的应用价值。     

基于改进BP网络的手写体汉字识别技术

研究了手写体汉字识别技术，采用改进BP算法进行网络训练，提高了算法的收敛速度。同时，利用神经网络完成了汉字识别系统的实现。实验表明系统较好地回避了汉字结构复杂、变形难以预测等问题，提高了识别效率。     

一种改进的LMS算法及其在自适应消噪中的应用

介绍了一种改进的LMS自适应滤波算法及其在自适应噪声对消中的应用。该算法利用误差信号的相关值去调节步长,解决了算法收敛时间与稳态误差间的矛盾,为实际应用提供了更大的灵活性。它同时实现了均方误差小和收敛速度快,并且降低了LMS算法对噪声的敏感性。文中最后给出了仿真结果,仿真结果与理论分析是一致的。     

基于遗传算法的协作优化方法研究

多学科设计优化技术是国内外迅速发展的一门学科,而协作优化方法是多学科设计优化技术中最常用的一种有效的分布式并行优化方法.然而,标准的协作优化方法很难收敛到系统的最优解,而且对初始点的选择非常敏感,不同的初始点可能收敛到不同的解.遗传算法是一种成熟的智能寻优算法,具有很强的全局搜索能力.本文正是为提高协作优化的可靠性和鲁棒性,将遗传算法引入协作优化框架,并且对传统遗传算法进行相应的改进以适用于协作优化框架.算例证明本文提出的基于遗传算法的协作优化方法行之有效,消除了标准协作优化可能收敛不到系统最优解及对初始点敏感的缺陷.     

噪声环境下鲁棒性语音特征提取的新方法

在本文中，我们提出一种噪声环境下具有鲁棒性的语音特征提取的新方法。首先介绍了在高噪声环境下语音识别所遇到的特殊问题，随后对现有的特征提取的方法做了比较，提出了基于线性预测的ＭＦＣＣ特征提取方法，通过实验比较证明该方法具有较好的鲁棒性     

智能结构不确定参数系统振动控制及其摄动分析

 结构建模中通常考虑不确定性等因素以确保系统及其控制系统具有良好的鲁棒性,由于参数不确定性引起的系统参数的变化将导致系统性能退化,甚至影响系统内部稳定性,所以不确定性概念在工程结构的分析与设计中起到重要的作用。研究了具有不确定参数系统鲁棒性理论,提出了抑制系统振动的控制规律;基于矩阵摄动法讨论了不确定参数对智能结构系统的影响,并利用不确定性凸模型理论分析了智能结构具有不确定参数系统稳定性的问题,提出了分析含不确定参数系统鲁棒性的方法。算例说明该方法的有效性。     

Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

提供流体动压滑动轴承-转子系统故障诊断深知识的振动参数识别方法

 转子的不平衡量、油膜的动态特性系数、调速器对转子作用力的系数是几个反映流体动压滑动轴承-转子系统故障的主要振动参数,提供这些参数作为故障诊断的深知识,可以有效地提高故障诊断专家系统的能力。本文给出了一个识别这些振动参数的方法,该方法简单、易行,适用于数据的实时处理。本文还给出了一个利用深知识进行故障诊断的实例。     

Parameter Optimization of a Nutation Damper Via the Second Method of Liapunov

The principle of parameter optimization of a linear time-invariant system via the second method of Liapunov is applied to optimize the parameters of a nutation damper suggested recently. Numerical results are derived, and it is indicated that the present values of optimum parameters agree closely with those obtained earlier by an approximate method.     

时间序列关联维数在非线性系统运动性态识别中的应用

 在非线性动力系统维数较高、数学模型难以建立时, 利用时间序列分维数对系统的动力学性质进行了研究。通过对一经典非线性方程的分析, 得出利用随参数变化的时间序列分维数图, 可以很好地识别非线性系统从确定性状态到分叉或浑沌状态的临界参数点或区域。最后将此方法应用于一单盘Jeffcott 转子模型的分叉参数点识别及一转子运动状态识别, 得到了比较满意的结果。     

Parameterization and adaptive control of space robot systems

In space application, robot system are subject to unknown or unmodeled dynamics, for example, in the tasks of transporting an unknown payload or catching an unmodeled moving object. We discuss the parameterization problem in dynamic structure and adaptive control of a space robot system with an attitude-controlled base to which the robot is attached. We first derive the system kinematic and dynamic equations based on Lagrangian dynamics and the linear momentum conservation law. Based on the dynamic model developed, we discuss the problem of linear parameterization in term of dynamic parameters, and find that in joint space, the dynamics can be linearized by a set of combined dynamic parameters; however, in inertial space linear parameterization is impossible in general. Then we propose an adaptive control scheme in joint space, and present a simulation study to demonstrate its effectiveness and computational procedure. Because most takes are specified in inertial space instead of joint space, we discuss the issues associated to adaptive control in inertial space and identify two potential problem: unavailability of joint trajectory because the mapping from inertial space trajectory is dynamic-dependent and subject to uncertainty; and nonlinear parameterization in inertial space. We approach the problem by making use of the proposed joint space adaptive controller and updating the joint trajectory by the estimated dynamic parameters and given trajectory in inertial space     

随机共振锁频环路影响因素

针对随机共振锁频环路影响因素不够明朗的问题,在对随机共振锁频环路仿真验证的基础上,重点对信噪比、采样频率和系统参数对环路性能的影响进行了探究。首先,阐述了随机共振锁频环路基本原理,搭建了随机共振锁频环路模拟仿真平台。其次,通过设定不同的信噪比、采样频率和系统参数条件,观察随机共振锁频环路性能变化。最后,总结归纳出各条件对随机共振锁频环路的影响。仿真结果表明,信噪比越低,随机共振锁频环路对信号跟踪性能越差,且最低能够处理信噪比为Eb/N0=1dB的信号。采样频率在高于信号频率50倍时,提高采样频率虽可提高计算精度,但对环路跟踪性能改善作用不大。系统参数是决定随机共振效应能否发生及影响共振效果的关键因素,其表现为一个可供选择的数值区间。     

Effects of flow parameters on thermal performance of an inner-liner anti-icing system with jets impingement heat transfer

The multiple jets impingement heat transfer is widely applied in the wing anti-icing system. It is challenging to apply the similarity criterion to carry out the anti-icing experiments due to the complex flow and heat transfer behavior. In the present study, the full-scale slat model is used to carry out anti-icing experimental researches in a 2 m × 3 m icing wind tunnel of China Aerodynamics Research and Development Center. The effects of icing parameters Liquid Water Content (LWC) and Median Volume Diameter (MVD) and hot air parameters (mass flow rate and temperature) on the thermal performance of an inner-liner anti-icing system with jets impingement heat transfer are studied. The effects of the experimental parameters are analyzed in detail by combining impingement and evaporation heat transfer mechanisms. The impingement hot air mass flow rate dramatically affects the heat transfer performance of the impingement stagnation region within the range of the experimental parameters. The temperature of impingement hot air and that of wing skin are approximately linear correlated. The experimental results show the effects of LWC and MVD on water film formation and runback ice accretion. The formation of water film is analyzed by an analytical method based on the wing skin temperature difference of dry and wet air conditions.     

Interstellar grains in the solar system: Requirements for an analysis

We discuss present knowledge about interstellar dust grains in the heliosphere in order to give goals for future investigations. As far as the identification of the interstellar flux from brightness observations is concerned we calculate the influence of interstellar dust entering the solar system on the Zodiacal light and Zodiacal emission brightness. In case of the Zodiacal light produced by the scattering of solar radiation, the brightness from interstellar dust within the solar system is not detectable within the limits of present observations. In the case of the thermal emission a distinction of the brightness from the interstellar dust component may be possible. This would be especially interesting for an analysis of the overall spatial distribution of the interstellar flux in the solar system. As far as the identification of the interstellar flux from impact experiments is concerned, parameters like the impact direction are essential. Since the interstellar dust flux is modified in the outer solar system already, it is helpful to probe its variation with increasing distance from the Sun in interstellar upstream direction.     

A Stratified Statistical Filter with Nonlinear Application

This paper introduces a statistical filter (or, more strictly, a filtering algorithm) which has intended application in the area of nonlinear systems. Within this context, the filter enables one to investigate the convergence effects produced by varying the initial estimates associated with the respective state variables, together with the various system parameters. The present algorithm is not intended to replace the more powerful optimal statistical filters used in linear theory, but rather to provide a simulation tool which can readily be applied to a given nonlinear system. The application considered in this paper bears a similarity to a tracking problem which might be encountered by an optical device, where angular information is the primary observable quanity. In this particular application, angular observations are available, and statistical estimates are desired for a position variable, together with an unknown parameter. The application is introduced primarily for the purpose of demonstrating the behavior of the filter when applied to a relatively simple nonlinear system.