基于Matlab系统辨识工具箱的系统建模

Matlab系统辨识工具箱的功能主要包括参数/非参数化模型辨识工具、模型验证工具、递推参数估计、各种模型类的建立和转换函数及集成多种功能的图形用户界面等.故基于该工具箱进行了系统建模,主要包括获取观测数据、数据预处理、选择模型结构、参数估计、模型检验与动态仿真等步骤.     

基于Matlab的PID参数最优化设计

PID参数的最优化设计通过单纯形法,利用Matlab的语句、图形功能、工具箱函数和最优化工具箱优化目标函数,构建动态系统,以简化动态仿真过程控制系统.多变量目标函数寻优用单纯形法,参数初值按控制理论确定,目标函数程序用仿真函数Sim编写.并以调节器参数最优化设计为例,论述了目标函数构造、初值确定、动态系统仿真分析的过程.     

基于Matlab的非线性控制仿真教学

基于Matlab的非线性控制仿真教学法用Matlab中的Simulink工具进行可视化动态仿真教学.并以单位负反馈控制系统动态结构图为例,引入饱和、死区与滞环等非线性环节,用Simulink建立系统仿真模型,通过选择仿真菜单及参数设置启动仿真过程,通过示波器观察系统的仿真效果.     

RBF神经网络在目标识别中的应用研究

基于递推最小二乘学习算法，提出了一种运用径向基函数神经网络进行目标识别的方法。仿真结果表明．该方法可以有效对来袭目标进行识别，具有较好的识别效果，对提高防空能力有一定的意义。     

基于遗传算法的动态矩阵预测控制算法

基于遗传算法的动态矩阵预测控制(DMC)算法在每个采样时刻,用遗传算法优化不同的染色体种群,由最优个体解码得到最优参数集,再计算当前控制序列增量并施加到被控对象.在下一时刻,由输出实测值修正初始预测值,直至结束为止.被控对象仿真表明,该算法具有较好的控制效果.     

基于HMM与K-均值聚类的声目标识别

提出一种隐马尔可夫模型和K-均值聚类混合模型的声目标识别方法.在该方法中,建立声信号的HMM,提取了声信号的线性预测系数（LPC）作为目标识别的参数,用K-均值算法对参数进行聚类,产生了训练和识别所用的特征向量.最后根据混合模型的识别算法判断声目标的类别.仿真结果表明：新的混合模型识别系统在声目标识别中具有可行性.     

考虑摩擦特性的机械手位置自适应切换控制

考虑摩擦特性机械手是不连续动态系统,其自适应切换控制器,是利用不连续系统扩展Lyapunov函数方法设计的.考虑到模型的参数未知及其参数摄动的存在,通过选取非光滑Lyapunov函数和辅助非定函数项,并利用barbalat引理进行系统稳定分析.该自适应切换控制器能使机械手在具有库仑摩擦力和出现参数摄动的情况下仍稳定在期望位置,实现位置调节.最后,对某二自由度机械手的Matlab软件仿真表明,该自适应切换控制器有效.     

逆M序列激励下石英挠性加速度计传递函数的时域建模

通过机理分析建立了石英挠性加速度计传递函数的数学模型,介绍了逆M序列参数选择的原则、辨识原理及算法的具体实现流程,并利用Matlab/Simulink库给出了算法的仿真验证.最后,搭建了加速度计数据采集系统,辨识其传递函数.该算法有很广的适用范围.     

异步电动机起动时动态参数的计算及变参数仿真

考虑到异步电动机起动过程中集肤效应对电机参数的影响，文章给出了异步电动机起动过程动态参数的计算方法，用Matlab／Simulink建立了变参数仿真模型，并对电机的起动过程进行了整体的仿真研究。仿真结果更接近于实际情况。     

基于动态规划和双变量容积卡尔曼滤波的空基外辐射源定位算法

针对空基外辐射源定位系统在杂波环境下的目标状态估计问题,提出一种基于动态规划和双变量容积卡尔曼滤波的空基外辐射源定位算法。基于误差传播理论,确定出目标的状态转移范围;选取回波信号幅度值作为动态规划的值函数进行递推积累;根据杂波的统计特性和极值理论解算出动态规划的目标量测提取阈值,逆向提取来自目标的量测序列;利用双变量容积卡尔曼滤波算法同时对目标和外辐射源进行状态估计。仿真结果表明：该算法不仅可以从杂波中有效地提取出目标量测序列,还能降低外辐射源状态不确定性对目标状态估计造成的影响,减少系统的计算量,具有良好的状态估计效果。     

Stability of the Third Generation Intensifier under Illumination

The stability under illumination of transmission-mode GaAs photocathode sealed in the third generation intensifier is investigated by use of spectral response testing instruments. The variations of spectral response with the illumination times under weak and intense illumination are compared. The variations of photoemission performance parameters are also characterized. The results show that during initial several weak illuminations photocathode behaves no evident decay and a maximum sensitivity is achieved, while under intense illumination the sensitivity of photocathode begin to decrease largely at the first illumination. The calculated performance parameters show that the variation of surface escape probability with illumination times is a direct cause of instability of photocathode. It is also found that under intense illumination peak wavelength is moved towards short-wave and peak response is decreased, which shows that the ability of long-wave response of photocathode is decreased.     

Passive Acoustic Radar for Detecting Supersonic Cruise Missile

A Passive Acoustic Radar is presented as a necessary complement to electromagnetic wave radar, which will be expected to be an effective means for detecting cruise missiles. Acoustic characteristics of supersonic flying projectiles with diverse shapes are expounded via experiment. It is pointed out that simulation experiment could be implemented using bullet or shell instead of cruise missile. Based on theoretical analysis and experiment, the ““acoustic fingerprint““ character of cruise missile is illustrated to identify it in a strong noise environment. After establishing a locating mathematical model, the technique of acoustic embattling is utilized to resolve a problem of confirming the time of early-warning, considering the fact that velocity of sound is much slower than that of light. Thereby, a whole system of passive acoustic radar for detecting supersonic cruise missile is formed.     

Design and Analysis of Test Schemes of Static Postponing Time on Shrapnels Used to Riot Control

The test scheme of static postponing time given in our actual national military test standard on shrapnels used to control riot is a nine-point test scheme on the combined action of three kinds of temperatures and three kinds of pressures,the consumed ammunitions are more excessive. Statistic analysis and tentative checkout about a lot of test data are done,feasibility gists are put forward for optimizing of the test design scheme. The optimizing design and data analysis of test scheme of the item are done by managing uniformity design theory, two scientific and reasonable six-point test schemes are confirmed. The feasibility and reliability of the optimizing design schemes put forward above are proved ulteriorly by test validating. The gained schemes not only have good design uniformity and little ammunition wastage and meet the test demand, but also have better forecast ability for the result data of other points using the mathematic models from the actual test points.     

Super-resolution Restoration of Remote-sensing Images

A novel image restoration scheme, which is super-resolution image restoration algorithm Poisson-maximum-afterword-probability based on Markvo constraint （MPMAP） combined with evaluating image detail parameter D, has been proposed. The advantage of super-resolution algorithm MPMAP incorporated with parameter D lies in the fact that superresolution algorithm MPMAP model is discrete, which is in accordance with remote-sensing imaging model, and the algorithm MPMAP is proved applicable to linear and non-linear imaging models with a unique solution when noise is not severe. According to simulation experiments for practical images, super-resolution algorithm MPMAP can retain image details better than most of traditional restoration methods; at the same time, the proposed parameter D can help to identify real point spread function （PSF） value of degradation process. Processing result of practical remote-sensing images by MPMAP combined with parameter D are given, it illustrates that MPMAP restoration scheme combined PSF estimation has a better restoration result than that of Photoshop processing, based on the same original images. It is proved that the proposed scheme is helpful to offset the lack of resolution of the original remote-sensing images and has its extensive application foreground.     

Design and Simulation of TF and TA Controller for Missile

A nonlinear terrain following(TF) and terrain avoidance(TA) controller is proposed for missile control systems. Based on classical TF algorithm (adaptive angle method), a new method for TF controller is proposed by using angle of attack. A method of obtaining terrain outline data from digital elevation map (DEM) for TF control is discussed in order to save store space. A TA algorithm is proposed by using bank-to-turn technique. The block control model, which is suitable for backstepping design, is given for nonlinear model of missile. Making full use of the characteristics of the system and combining block control principle and backstepping technique, a robust controller design method is proposed. Uncertainties in every sub-block are allowed, and can be canceled by using the idea of nonlinear damping. It is proved that the state tracking errors are converged to a neighborhood of the origin exponentially. Finally, nonlinear six-degree-of-freedom simulation results for the missile model are presented to demonstrate the effectiveness of the proposed control law.     

Design of Non-fragile Satisfactory Estimator for Linear Continuous Perturbed Stochastic Systems

The design problem of non-fragile estimator is addressed for a class of perturbed linear continuous systems. The perturbations occur on the plant and estimator parameters. The estimator designed should force the error system to achieve the desired decay rate and force the steady error variance less than the specified upper bound irrdevancy of the admissible plant perturbations and estimator perturbations. Consistency problem of the decay rate with the variance upper bound is first considered via linear matrix inequality （LMI） approach. The solution of the estimator parameter under specifications to be consistent is then discussed. The consistency condition of specifications and estimator parameter solution are transformed to feasible or minimum problems subject to a set of LMI respectively. The method is illustrated by a numerical example.     

An Improved Scene-based Nonuniformity Correction Algorithm for Infrared Focal Plane Arrays Using Neural Networks

The improved scene-based adaptive nonuniformity correction （NUC） algorithms using a neural network （NNT） approach for infrared image sequences are presented and analyzed. The retlna-like neural networks using steepest descent model was the first proposed infrared focal plane arrays （IRFPA） nonuniformity compensation method, which can perform parameter estimation of the sensors over time on a frame by frame basis. To increase the strength and the robustness of the NNT algorithm and to avoid the presence of ghosting artifacts, some optimization techniques, including momentum term, regularization factor and adaptive learning rate, were executed in the parameter learning process. In this paper, the local median filtering result of Xij （ n ） is proposed as an alternative value of desired network output of neuron Xij （ n ）, denoted as Tij （ n ）, which is the local spatial average of Xij （ n ） in traditional NNT methods. Noticeably, the NUC algorithm is inter-frame adaptive in nature and does not rely on any statistical assumptions on the scene data in the image sequence. Applications of this algorithm to the simulated video sequences and real infrared data taken with PV320 show that the correction results of image sequence are better than that of using original NNT approach, especially for the short-time image sequences （several hundred frames） subjected to the dense impulse noises with a number of dead or saturated pixels.     

Piecewise Filter of Infrared Image Based on Moment Theory

The disadvantages of IR images mostly include high noise, blurry edge and so on. The characteristics make the existent smoothing methods ineffective in preserving edge, To solve this problem, a piecewise moment filter （PMF） is put forward. By using moment and piecewise linear theory, the filter can preserve edge. Based on the statistical model of random noise, a related-coefficient method is presented to estimate the variance of noise. The edge region and model are then detected by the estimated variance. The expectation of first-order derivatives is used in getting the reliable offset of edge. At last, a fast moment filter of double-stair edge model is used to gain the piecewise smoothing results and reduce the calculation. The experimental result shows that the new method has a better capability than other methods in suppressing noise and preserving edge.     

Bistatic Sonar Localization Based on Best Linear Unbiased Estimation

A best linear unbiased estimation （BLUE） algorithm for bistatic sonar localization is proposed. The Cramer-Rao bound for bistatic Sonar and the geometrical dilution of precision （GDOP） in different conditions are given. The simulation results show that the location accuracy of BLUE algorithm is higher than the weighted least square method.     

Research on Gear-broken Fault Diagnosis in a Tank Gearbox

A fault diagnosis method of working position gear in a tank gearbox is put forward based on simulating the fault of working position gear in an actual tank, extracting the envelope of vibration signal by Hilbert transformation amplitude demodulation method, and zooming the low-frequency band to envelope signal.