递阶自校正飞行控制

一、引言 飞行器控制最初只作了三个单独回路独立控制,随着飞行事业的发展,又考虑三个独立的自适应回路以适应飞行环境的变化。但飞行器三个通道六个自由度之间是互相耦合的,考虑变量之间耦合集中控制,系统过于复杂难以实时控制。     

非常规机动操纵要求的计算

首先推导了飞机运动的逆动力学模型，为使问题具有一般性，采用了刚体运动模型，其中力方程建立在风轴系中，力矩方程建立在体轴系中，并且已知气动力模型，其次，由于飞行轨变地标位置（ｘ，ｙ，ｚ）的形式给出，因此构造了一种基于坐标位置的算法，当给定坐标值后，即可据此对逆问题进行求解并得出相应的操纵要求，最后以一种非常规机动动作为例进行了逆仿真，得出了操纵要求。     

Nonlinear adaptive and sliding mode flight path control of F/A-18 model

The question of inertial trajectory control of aircraft in the three-dimensional space is discussed. It is assumed that the nonlinear aircraft model has uncertain aerodynamic derivatives. The control system is decomposed into a variable structure outer loop and an adaptive inner loop. The outer-loop feedback control system accomplishes (x,y,z) position trajectory and sideslip angle control using the derivative of thrust and three angular velocity components (p,q,r) as virtual control inputs. Then an adaptive inner feedback loop is designed, which produces the desired angular rotations of aircraft using aileron, elevator, and rudder control surfaces to complete the maneuver. Simplification in the inner-loop design is obtained based on a two-time scale (singular perturbation) design approach by ignoring the derivative of the virtual angular velocity vector, which is a function of slow variables. These results are applied to a simplified F/A-18 model. Simulation results are presented which show that in the closed-loop system asymptotic trajectory control is accomplished in spite of uncertainties in the model at different flight conditions.     

Polynomial Representation of NURBS and Its Application to High Frequency Scattering Prediction

This article presents a method that uses physical optics (PO) techniques to compute the monostatic radar cross section (RCS) of electrically large conducting objects modeled by non-uniform rational B-spline (NURBS) surfaces. At the beginning, a new algorithm to convert recursive B-spline basis function into piecewise polynomials in power form is presented. Then, algorithm computes the polynomial representation of B-spline basis functions and NURBS surface geometric parameters are obtained. The PO integral over NURBS surfaces of an electrically large conducting object is used to predict the object's RCS. The NURBS surface is divided into small piecewise polynomial parametric patches by isoparametric curves, and the PO integral expression over the parametric domain of each polynomial parametric patch is reduced to an analytical expression which permits an accurate and effective computation of the PO integral by using a modified Ludwig's algorithm. The RCS of the object can be obtained by adding up the PO integral contribution of each polynomial parametric patch. The effectiveness of this method is verified by numerical examples.     

Velocity Estimation from Position Outputs of a Three-Dimensional Radar

Kalman filtering equations to obtain estimates of velocity from radar position information are defined. In a track-while-scan operation, a three-dimensional radar sensor measures range, bearing, and elevation (r, ?, ?) of an airborne target at uniform sampling intervals of time T. The noisy position measurements are converted to x, y, z coordinates and put through a Kalman filter to obtain x, y, z velocity components. The filtering equations together with steady-state error estimates are given.     

Analytical solution of discrete colored noise ECA tracking filter

New analytical solutions of steady-state Kalman gains are presented for a discrete-time tracking filter with correlation in both the measurement noise and the target maneuver. The measurement noise model is a first-order discrete Markov process characterized by a correlation coefficient ρ. The target motion is examined for an exponentially correlated acceleration maneuver type in which the vehicle oscillation such as wind-induced-bending is also considered. The present solution method is based on factorizing the observed spectral density matrix Ψ(z) in frequency domain. The algorithm proposed here gives the Kalman gain matrix directly. For a case when the steady-state error covariance matrix is desired, such gains can be incorporated with the algebraic Riccati equation     

三角形幅度激励的单脉冲阵列方向图

 文中讨论了离散元等间距排列成单脉冲阵列的和差方向图函数。激励幅度的包络是等幅、三角形和倒三角形（V形）分布。人们利用Z变换法或有限Z变换法已获得了紧凑的阵因子表达式（4）,S（z）=F（2）-G（z）。这里利用G（z）简洁公式（8）,有时兼用位移定理,只以单边Z变换求出S（z）,而不管包络函数对称与否。给出了计算例子。对和方向图还进行了实验研究,在主波瓣范围内实测数据同计算结果吻合得较好。差方向图也被实验验证过。     

An Approach to Fixed-Point Smoothing Problems

This paper examines the possibility of deriving fixed-point smoothing algorithms through exploitation of the known solutions of a higher dimensional filtering problem. It is shown that a simple state augmentation serves to imbed the given n-dimensional smoothing problem into a 2n-dimensional filtering problem. It is further shown that computation of the smoothed estimate and the corresponding error covariance does not require implementation of the 2n-dimensional filtering equations. Some new results involving systems with or without multiple time delays and having colored observation noise have been derived in order to illustrate the versatility of the proposed technique. It is also demonstrated that the present approach leads to an easier derivation of the continuous-time fixed-point smoothing algorithm reported in the literature.     

Dynamics of the Phase-Locked Loop without a Limiter

The general (nth order) phase-locked loop is analyzed, of which the amplitude is not constant. The input carrier signal is amplitude-modulated by wide-band stationary Gaussian noise, and the signal, superposed with the additive white stationary Gaussian noise, enters the nonlimited phase-locked loop. Under the above assumptions the loop can be shown to constitute an n-dimensional vector Markov process, so that the process satisfies the n-dimensional Fokker-Plank equation. The probability density function depends on the effective loop signal-to-noise ratio and the effective modulation power.     

模糊超体神经网络及其在火箭发动机故障分离中的应用

提出了一种用模糊集表示火箭发动机故障模式的神经网络二次分离器,模糊集是由模糊超体聚集形成的集合体,模糊超体在一次分离中表现为由半径和球心确定的n维超球,在二次分离中是一个由夹角、球心和方向矢量确定的部分超球。神经网络二次分离学习算法与一次学习算法相比,提高了训练样本的分离精度,增强了神经网络对故障的敏感性。      

混合遗传算法及其在叶片自动优化设计中的应用

 在遗传算法中 ,采用单纯形法寻优取代变异运算构成混合遗传算法 ,以提高遗传算法局部搜索能力。算例表明混合遗传算法可有效提高搜索效率和对最优解的逼近程度。采用三次多项式和多圆弧方法生成叶型中弧线 ,三次多项式分布叶型厚度 ,对叶型进行参数化。将N S方程正问题流场数值计算与混合遗传算法相结合 ,构成叶轮机械叶型自动优化设计。尝试由气流转角、总压损失和叶型型面面积构成目标函数 ,对压气机叶型进行自动优化设计。     

一种空中交通图象特征匹配方法

提出了一种确定飞机类型的新方法。通过 机外型和结构特征，利用空间投影理论建立了飞机投影图形与飞机姿态角之间的关系。通过该关系方程，有效地识别了飞机姿态角。利用已有的飞机型的投影图特征与实际飞机飞行图像特征之间的误差，根据最小方差进行了模型匹配。利用ＣＣＤ系统图像仿真结果表明，所提出的方法是有效的。     

几何规划在飞机总体设计中的应用

系统地讨论了代数多项式的算术－ 几何均值定理,并对原型几何规划理论作出了简明的推导与分析。提出了具有缩并迭代特性的几何规划求解理论和编程步骤。还用２ 个工程设计的优化求解算例来说明这种缩并迭代几何规划优化求解特点和优点。例１ 显示了几何规划的工程实用性和简易性;例２ 通过轻型飞机总体方案参数优化,说明所提出的优化方法,可随设计人员思路的变动而得到及时地相适应。     

二重积分中值定理中间点的进一步讨论

众所周知,二重积分中值定理一般表述为：“设Ｄ为平面上有界闭区域,ｆ（ｘ,ｙ）在Ｄ上连续,ｇ（ｘ,ｙ）在Ｄ上可积且不变号,则至少存在一点（ζη）∈Ｄ,使得∫∫Ｄｆ（ｘ,ｙ）ｇ（ｘ,ｙ）ｄｘｄｙ＝ｆ（ζη）∫∫Ｄｇ（ｘ,ｙ）ｄｘｄｙ。”进一步证明了中间点（ζη）可选为Ｄ的内点,其结论与方法完全可推广到一般多重积分中值定理。     

概率疲劳损伤力学的四参数Lognormal模型

 基于由宏观角度综合概率统计方法、疲劳研究及损伤力学三者建立的概率疲劳损伤力学PFDM(Probabilistic Flatigue Damage Mechanics)基本模型,考虑到工程中常用的Lognormal概率分布,经过大量的简化和推导,初步建立起适合于工程中常幅疲劳问题的Lognormal分布四参数PFDM模型,文中讨论了损伤参量D_(eq)、相对梯度RG的具体形式,在获取PFDM基本材料参数的前提下,可以对实际构件的疲劳寿命的Lognormal概率分布进行估算,文中还就40Cr调质钢、LY12CZ材料给出实例。     

液晶在冲击冷却研究中的应用

 本文利用胆甾型液晶的温色效应,对孔径d=2.4mm,孔间距比xn/d=5,yn/d=6.67的7×10个射孔的多股射流冲击冷却进行了试验研究。在同一个总射流流量下,当孔排方式为顺排和叉排,孔至靶面的距离Z/d=1.08,2.16,3.25时,热图象显示的结果表明:顺排孔的冲击冷却效果比叉排的好,乳至靶面的距离在Z/d=2.16时的冷却效果最好。同时也获得了多股射流冲击冷却的对流换热系数等值线谱图。     

An efficient and globally optimal solution to perspective-n-line problem

This research develops an accurate and efficient method for the Perspective-n-Line(Pn L)problem. The developed method addresses and solves Pn L via exploiting the problem’s geometry in a non-linear least squares fashion. Specifically, by representing the rotation matrix with a novel quaternion parameterization, the Pn L problem is first decomposed into four independent subproblems. Then, each subproblem is reformulated as an unconstrained minimization problem, in which the Kronecker product is a...     

模糊极小极大神经网络在火箭发动机故障分类中的应用

研究了一种用模糊集表示火箭发动机故障模式的神经网络分类器。模糊集是由模糊超立方体聚集形成的集合体，模糊超立方体是一个极小点和极大点构成的用隶属函数表示的ｎ维方盒。极小点和极大点的确定用包含有扩张与收缩阶段的模糊极小极大学习算法实现，这种算法能在一次循环学习中形成非线性模式边界，无需对已知故障模式重新训练就可融合新样本和精炼已存在的故障模式。模糊集用于故障模式分类自然地提供了故障更刘水平分类的有用信     

基于左矩阵分式模型的模态参数识别方法

提出一种多输入多输出(MIMO)系统的宽频模态参数识别算法。该方法基于频响函数(FRF)的左矩阵分式模型(LMFD),通过最小二乘法在z域内求解模态参数,避免了s域内矩阵的病态问题。针对左矩阵分式模型的特点,给出了一种通过主分量分析(PCA)建立稳定图的方法。指出了传统的频域多参考点(PRFD)方法与基于左矩阵分式模型识别方法之间的关系。最后采用GARTEUR模型仿真算例与飞机模型的实测算例对所提出的方法进行了验证,结果表明该方法具有良好的识别效果。     

基于单轴速率转台的捷联惯测组合标定方法

针对传统的"位置+速率"捷联惯测组合(SIMU)标定方法标定时间长、对标定设备要求高,且需要北向基准等问题,提出了基于单轴速率转台的捷联惯测组合标定方法。该标定方法只用一台单轴速率转台。捷联惯测组合3个轴分别垂直向上及向下时转台匀速旋转一圈,通过对单轴速率转台的姿态角及捷联惯测组合测量模型进行适当的数学变换,分离出捷联惯测组合的误差系数。建立了标定模型,推导了误差系数的分离算法,编排了标定流程,给出了数据处理方法,通过试验验证了方法的有效性。该方法对标定设备要求低,无需北向基准,标定时间短,适合于中等精度捷联惯测组合的标定。