A practical filter error method for aerodynamic parameter estimation of aircraft in turbulence

It is common for aircraft to encounter atmospheric turbulence in flight tests. Turbulence is usually modeled as stochastic process noise in the flight dynamics equations. In this paper, parameter estimation of nonlinear dynamic system with both process and measurement noise was studied, and a practical filter error method was proposed. The linearized Kalman filter of first-order approximation was used for state estimation, in which the filter gain, along with the system parameters and the initial states, constituted the parameter vector to be estimated. The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method, and the sensitivities of observations to unknown parameters were calculated by finite difference approximation. Some practical aspects of the method application were discussed. The proposed filter error method was validated by the flight simulation data of a research aircraft. Then, the method was applied to the flight tests of a subscale aircraft, and the aerodynamic stability and control derivatives were estimated. All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach. It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.     

Efficient adaptive Kriging for system reliability analysis with multiple failure modes under random and interval hybrid uncertainty

In the field of the system reliability analysis with multiple failure modes, the advances mainly involve only random uncertainty. The upper bound of the system failure probability with multiple failure modes is usually employed to quantify the safety level under Random and Interval Hybrid Uncertainty(RI-HU). At present, there is a lack of an efficient and accurate method for estimating the upper bound of the system failure probability. This paper proposed an efficient Kriging model based on nume...     

基于T-S模糊模型的非线性分布参数系统极点配置P-sD控制CSCD

采用Lyapunov直接法讨论分布参数系统的稳定性,建立分布参数系统的Lyapunov函数。为保证分布参数系统稳定,应使Lyapunov函数对时间的微分小于0。由于分布参数系统中存在空间一次微分项与二次微分项,Lyapunov函数对时间的微分中将出现常数项与积分项,针对常数项,引入空间一次微分项来抵消;针对积分项,引入对应的状态反馈来使系统稳定。利用边界条件量化Lyapunov函数对时间的微分中的各项,从而设计控制器,这是一种新的设计P-sD状态控制的方式。其中状态反馈的部分采用极点配置的方法来设计,当分布参数系统中出现状态变量的非线性函数时,采用T-S模糊模型表达,可以通过状态变量的线性组合精确描述非线性项,以便极点配置设计状态反馈。针对两个非线性分布参数数学模型进行仿真,结果证明设计的P-sD状态控制器可以使分布参数系统稳定,并达到期望的效果。     

一种嵌入式网络视频服务器的研究与实现

介绍一种基于嵌入式处理器的网络视频服务器。该系统采用Motorola ARM9处理器和嵌入式L inux操作系统,利用软件实现图像的采集、压缩和网络传输。试验证明,该方案用于视频监控是可行的。     

基于独立函数的通用逻辑模块

本文提出一种新型的通用逻辑模块(ULM),它以独立函数为核心(细胞),细胞之间以相同的方式——“异或”——相联结,可以生成全部2~(2n)个逻辑函数。它具有算法简单、使用灵活的特点。在伪随机信号的产生及自动控制中有着广阔的应用前景。     

柔性喷管力矩特性的识别

本文在试验、测量、计算获得柔性喷管的总力矩—摆角响应曲线的基础上,对其物理特性作了分析,建立了辨识其力矩特性的数学模型。利用三次样条函数的特点,较准确地再现了该数学模型所代表的矛盾方程组,然后又利用多元线性回归分析,最终求得了组成总力矩的弹性力矩,粘滞摩擦力矩、库伦摩擦力矩、惯性力矩和偏位力矩等以及它们的力矩系数。并在计算机上进行了仿真试验,对建立的数学模型和分析方法作了验证。     

再入航天飞机表面热流密度辨识

本文给出了求解表面热流密度辨识这一热传导逆问题的顺序函数法。然后以某模型航天飞机迎风中心线上的某特征点为例，将航天飞机再入时的表面热流密度辨识问题简化为一维模型问题，用顺序函数法来对该特征点上的对流加热流密度进行了仿真辨识，得到了较理想的辨识结果。该方法在航天研究领域有着良好的工程应用前景。     

MTFC在光学遥感成像系统优化设计中的应用研究

图像处理作为成像链路的重要组成部分，是系统优化设计不得不考虑的一个环节，其中调制传递函数补尝（MTFC）是当今研究的热点，在遥感成像系统优化设计中发挥着重要作用。如果综合应用地面MTFC的能力，对遥感器进行优化设计，则可以大大减轻遥感器的研制难度、节约成本和缩短研制周期。该文对MTFC在光学遥感成像系统优化设计中的应用进行了一些探讨。