自适应设计空间扩展的高效代理模型气动优化设计方法

对基于Kriging模型气动优化的加点方法和设计空间的构建问题进行了研究。首先,针对高效全局优化（EGO）方法收敛缓慢的问题,提出了一种混合加点方法,该方法通过引入期望提高（EI）阈值控制EI和最小预测值（MP）加点准则,利用先全局再局部的优化思想,提高了EGO方法在确定设计空间内的收敛性。其次,针对设计空间的构建问题,对比了扩大设计变量范围和多轮优化两种不同的设计空间构建方法,分析了设计变量范围对设计空间大小和样本密度的影响,进而提出了自适应设计空间扩展的代理模型优化方法。相对于传统固定设计空间的方法,自适应设计空间扩展的方法在动态的设计空间中进行优化搜索,只在有潜力的维度扩展设计变量范围,通过构建自适应设计空间,实现了样本的高效配置。最后,通过ADODG标准翼型优化算例证实,自适应设计空间优化方法可以大幅提高气动优化设计效率。     

基于辅助变量最小二乘的无人艇模型辨识方法

无人艇模型是无人艇运动控制研究领域的核心,模型的精确性对控制算法的设计及验证有很大的影响.为了解决有色噪声对无人艇模型参数辨识时的干扰问题,提出了一种辅助变量最小二乘算法对无人艇模型参数进行辨识.对离散KT方程加入噪声,得到无人艇时间序列分析模型,根据Tally原理引入辅助变量对最小二乘算法进行完善并辨识模型参数.所做...     

简谐力激励下多组件结构系统的整体优化设计

多组件结构系统整体优化设计通过协同优化支撑结构拓扑构型和组件布局来使结构系统的位移响应最小。本文提出通过模态加速度法（MAM）求解多组件结构系统的位移响应,并以位移响应值最小作为优化目标;引入多点约束（MPC）方法模拟组件与设计域间的铆钉或螺栓连接形式;采用有限包络圆法（FCM）来避免组件之间及组件与设计域边界产生干涉。建立了多组件结构系统整体优化问题的数学模型,并对动响应目标函数关于设计变量的灵敏度进行了推导。最后,通过几个算例验证了整体优化方法在简谐力激励下求解问题的可行性及其在实际问题中的有效性。     

多变量系统参数辨识的相关分析法

 <正> 近20年来,线性系统的辨识和参数估计的研究工作得到了迅速发展。系统辨识的方法主要有:最小二乘法、广义最小二乘法、推广最小二乘法、多级最小二乘法、辅助变量法、随机逼近法、极大似然法以及相关分析法等。在这些方法中,相关分析法是一种公认最有效的算法。1974年,Iserman、Saridis和Sinha等人通过若干数值算例证实     

基于新型高维代理模型的气动外形设计方法

随着现代飞行器性能需求的不断提高，飞行器精细化气动优化设计要求更高可信度的CFD数值分析及更多的独立设计变量，使得基于代理模型的全局优化算法在超过一定的设计变量后显著降低了效率，难以满足复杂工程的设计需求。而目前的高维代理模型过程复杂、时间花费高，缺乏对工程问题的广泛适应性。针对以上难题，提出了利用监督式非线性降维代理建模方法来缓解代理优化过程中的高维变量设计难题。该方法将核主成分分析（非线性）降维与高斯回归过程模型统一训练，自适应构建新型高维代理模型，并随着优化过程不断学习改进模型，建立了从高维输入到输出的准确映射，有效解决了传统高维代理模型训练时间花费高和适应性差等难题。然后基于该新型代理模型发展了适用于飞行器复杂气动设计的高维全局优化设计方法，并将其应用到美国航空航天学会（AIAA）优化小组发布的2个复杂跨声速优化算例中。通过与传统代理优化方法全面比较，验证了所提的方法能大幅提高飞行器高维变量全局优化效率和全局寻优能力。     

基于复合优化的航空发动机模型参数估计

本文提出了一种复合优化方法,用于发动机多变量,状态空间模型的时域辨识。优化中粒子群优化算法和最小二乘优化算法按照“串联”方式运行。粒子群优化从一个初始种群出发,通过进化来搜索最优解。然而有些时候,粒子群算法会陷入次优解。那么最小二乘优化算法就可以从粒子群的次优解出发,通过共轭梯度法获得问题的最优解。本方法适用于待估计参数较多,且参数变化范围大的高阶多变量系统。本文将复合优化算法用于4输入4输出状态变量模型参数的估计。仿真结果表明了所提出方法的有效性。     

基于最小二乘法的GPS故障星辨识新方法研究

在最小二乘故障检测的基础上,提出了一种在最小二乘法残差向量ω的似然函数基础上推导出故障卫星辨识的新方法。采用该方法针对GPS卫星中可能出现的突发性故障以及斜坡形软故障进行了仿真实验。结果表明,该故障卫星辨识方法能够准确地辨识出故障卫星并将其实时剔除,星座重构后能够使GPS的定位莰差处于正常的范围内。     

辨识传递函数模型的应用程序及技术问题探讨

我们用BASIC语言设计了根据频响数据辨识传递函数模型（以下简称模型）的应用程序。在计算机上对八个模型的频响数据进行了辨识,结果较吻合。 一、原理和误差判定准则 1.原理 应用最小二乘原理,使试验结果C（jω₁）和辨识结果G_a（jω₁）的误差平方和为最小。      

一种无人机荷兰滚模态辨识方法研究

针对某无人机无法测量侧滑角的问题,提出一种基于偏航角速率的荷兰滚模态低阶等效拟配方法。采用倍冲信号对荷兰滚模态进行激励,基于推导所得等效模型,采用最小二乘法进行频域优化,得到了某无人机在姿态遥控模式下的荷兰滚模态特性。结合飞行操作员评价表明:所采用的辨识方法适用于没有侧滑角传感器,且处于姿态遥控模式下的无人机荷兰滚模态特性辨识。     

动力翼伞系统空投风场的辨识与应用

风场对动力翼伞系统的运动状态有着重要的影响,获得风场中风的速度和方向可以使动力翼伞系统利用或者消除风场的影响。针对风场辨识问题,通过分析动力翼伞系统在风场作用下的飞行特性,提出了一种基于动力翼伞系统在风中的飞行状态进行风场辨识的方法。该方法仅使用动力翼伞系统配备的全球定位系统（GPS）模块采集定位数据,计算获得动力翼伞系统飞行的速度和方向,根据风场与动力翼伞系统的动态关系,利用最小二乘法对风场进行在线辨识。为了保证辨识精度,由GPS获得的动力翼伞系统运动信息经卡尔曼滤波器进行滤波处理。仿真结果表明：该方法对风场有较高的辨识效果,并能辅助实现雀降。     

Variability of GPS satellite differential group delay biases

An important issue in determining the accuracy of global positioning system (GPS) satellite ionospheric measurements is the instrumental delay biases between the L-band frequencies in both the satellites and the receivers. These differential L1-L2 biases must be measured and removed from the GPS measurements before an accurate estimate of the total electron content can be obtained. The results from the measurements indicate that the day-to-day variations of the satellite differential biases are quite well over a five-week time span, with a variation of less than 0.3-ns differential delay (one sigma). A follow-up experiment conducted two years later showed that the satellite biases had not changed significantly over this longer time span. When the prelaunch calibration values are compared with the experimental bias estimates, two of the four satellite pairs show excellent agreement and two differ significantly, indicating that prelaunch calibrations should be used with caution.<>     

Bearings-only and Doppler-bearing tracking using instrumentalvariables

In bearings-only tracking (BOT) or Doppler and bearing tracking (DBT), both common passive sonar problems, the measurement equations are nonlinear. To apply the Kalman filter, it is necessary either to linearize the equations or to embed the nonlinearities into the noise terms. The former sometimes leads to filter divergence, while the latter produces biased estimates. A formulation of BOT and DBT which has a constant state vector and simplifies the tracking problem to one of constant parameter estimation is given. The solution is by the instrumental variable method. The instrumental variables are obtained from predictions based on past measurements and are therefore independent of the present noisy measurements. The result is a recursive unbiased estimator. The theoretical developments are verified by simulation, which also shows that the formulation leads to near optimal estimators whose errors are close to the Cramer-Rao lower bound (CRLB)     

Longitudinal parameter identification of a small unmanned aerial vehicle based on modified particle swarm optimization

This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle(UAV)through modified particle swam optimization(PSO).The procedure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems(MEMS)inertial measuring element and a global positioning system(GPS)receiver to provide test information.A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration(SRPSO).Once modified PSO is applied to the mathematical model,the simulation results show that the mathematical model is correct,and aerodynamic parameters and coefficients of the propeller can be identified accurately.Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV.Some parameter identification results are affected slightly by noise,but the identification results are very good overall.Eventually,experimental validation is employed to test the proposed method,which demonstrates the usefulness of this method.     

PI controller relay auto-tuning using delay and phase margin in PMSM drives

This paper presents an auto-tuning method for a proportion plus integral（PI） controller for permanent magnet synchronous motor（PMSM） drives, which is supposed to be embedded in electro-mechanical actuator（EMA） control module in aircraft. The method, based on a relay feedback with variable delay time, explores different critical points of the system frequency response.The Nyquist points of the plant can then be derived from the delay time and filter time constant.The coefficients of the PI controller can then be obtained by calculation while shifting the Nyquist point to a specific position to obtain the required phase margin. The major advantage of the autotuning method is that it can provide a series of tuning results for different system bandwidths and damping ratios, corresponding to the specification for delay time and phase margin. Simulation and experimental results for the PMSM controller verify the performance of both the current loop and the speed loop auto-tuning.     

基于改进准则法的复合壳阻尼结构拓扑减振动力学优化

针对复合壳阻尼结构的拓扑减振优化问题，以约束阻尼层的有限单元为设计变量，采用体积比、模态频率和振型为优化约束条件，构建以多模态权重系数的结构模态损耗因子数值关系为优化目标函数的拓扑减振优化模型。为了拓展优化目标灵敏度具有不局限于某一变密度法插值模型的形式，推导了数值表达式的一般函数式。动力学优化中优化目标灵敏度正、负数集共存，使得非凸性的目标函数设计变量出现负值或优化函数寻优于局部极值点。为此，推导出复合壳阻尼结构的全域灵敏度改进优化准则法迭代格，以确保每次迭代域均为全域设计变量集。结合有限单元法编程实现了复合壳阻尼结构改进准则法，并对复合壳结构进行拓扑减振优化分析。结果表明：在敷设体积减为全覆盖的50%时，复合壳结构的模态损耗因子增减偏差为10%，具有提升减振的轻量化设计目的；各阶目标函数和拓扑构型所需的迭代次数少，中间密度区域较小，多阶优于单阶模态优化函数，易于获得全域寻优的有效减振。     

Instrumental variable adaptive array processing

An instrumental variable (IV) approach is presented for estimating the weights of an adaptive antenna array. Theoretical analysis of the IV method shows that the antenna gain weights are independent of finitely correlated noise, so that unbiased estimation of signal arrival angles is possible. Only matrix inversions are required to compute the weight estimates. In this sense, the IV method provides performance comparable with eigenvector techniques but with lower computational burden. Both minimal and overdetermined IV estimators are derived. The overdetermined estimators give the same theoretical array weights as minimal estimators, but yield more accurate weight estimates in real data situations. Simulation results are presented to compare these IV methods with one another and with conventional matrix inversion weight estimators. In these examples it is seen that IV methods are able to resolve closely spaced interference sources when conventional matrix inversion techniques cannot. It is also shown that overdetermined methods are capable of providing weight estimates with lower variances than those of minimal methods     

用改进的辅助变量法识别非定常气动力系数

辅助变量法是一种域识别线性系统动态参数的常用方法，在噪声强度较大时，常得不到稳定的收敛解，本文通过在其迭代过程中引入加权函数，构成了该方法的一种改进方法，为检验改进方法的有效性，对仿真的振动系统和风洞实验获取的振动向应进行了气动力系数的同步识别。结果表明：甚至在噪声强度高达１５％情况下，改进后的方法仍能得到较好的收敛解。     

航空发动机过渡态全局寻优控制方法研究

为了对发动机的动态过程进行控制, 提出了一种基于SQP的全局寻优控制方法.每一步寻优过程分为长程优化和短程优化两个阶段.根据长程优化结果, 重构了关联目标函数, 在此基础上, 进行了短程优化修正, 并利用修正结果进行控制.将这种方法应用于某型航空发动机的过渡态控制中, 得到了理想的控制结果.仿真结果表明该方法能较好地解决一般局部优化方法在有纯延迟、模型失配等情况下的优化控制效果下降的问题.      

基于神经网络与果蝇优化算法的涡轮叶片低循环疲劳寿命健壮性设计

在对涡轮叶片低循环疲劳寿命概率分析的基础上,将广义回归型神经网络(generalized regression neural network,GRNN)与果蝇优化算法(fruit fly optimization algorithm,FFOA)结合,利用果蝇优化算法的多点全局的快速搜索能力来优化影响疲劳寿命的随机变量,进行涡轮叶片低循环疲劳寿命健壮性优化设计.优化结果表明:疲劳寿命的概率区间减小17.9%,对随机变量的敏感度降低,从而可以更精确地对疲劳寿命进行估计.计算结果验证了该方法在工程应用中的可行性.      

An efficient aerodynamic shape optimization of blended wing body UAV using multi-fidelity models

This paper presents a novel optimization technique for an efficient multi-fidelity model building approach to reduce computational costs for handling aerodynamic shape optimization based on high-fidelity simulation models. The wing aerodynamic shape optimization problem is solved by dividing optimization into three steps—modeling 3D(high-fidelity) and 2D(lowfidelity) models, building global meta-models from prominent instead of all variables, and determining robust optimizing shape associated with tuning local meta-models. The adaptive robust design optimization aims to modify the shape optimization process. The sufficient infilling strategy—known as adaptive uniform infilling strategy—determines search space dimensions based on the last optimization results or initial point. Following this, 3D model simulations are used to tune local meta-models. Finally, the global optimization gradient-based method—Adaptive Filter Sequential Quadratic Programing(AFSQP) is utilized to search the neighborhood for a probable optimum point. The effectiveness of the proposed method is investigated by applying it, along with conventional optimization approach-based meta-models, to a Blended Wing Body(BWB) Unmanned Aerial Vehicle(UAV). The drag coefficient is defined as the objective function, which is subjected to minimum lift coefficient bounds and stability constraints. The simulation results indicate improvement in meta-model accuracy and reduction in computational time of the method introduced in this paper.