Start-up current adaptive control for sensorless high-speed brushless DC motors based on inverse system method and internal mode controller

The start-up current control of the high-speed brushless DC (HS-BLDC) motor is a chal-lenging research topic. To effectively control the start-up current of the sensorless HS-BLDC motor, an adaptive control method is proposed based on the adaptive neural network (ANN) inverse system and the two degrees of freedom (2-DOF) internal model controller (IMC). The HS-BLDC motor is identified by the online least squares support vector machine (OLS-SVM) algo-rithm to regulate the ANN inverse controller parameters in real time. A pseudo linear system is developed by introducing the constructed real-time inverse system into the original HS-BLDC motor system. Based on the characteristics of the pseudo linear system, an extra closed-loop feed-back control strategy based on the 2-DOF IMC is proposed to improve the transient response per-formance and enhance the stability of the control system. The simulation and experimental results show that the proposed control method is effective and perfect start-up current tracking perfor-mance is achieved.     

基于边际效用理论的飞机维修模式的探讨

为提高飞机维修的经济性,采用经济学领域的边际效用理论对飞机维修效用、维修边际效用和维修总效用进行了定义,为量化飞机维修效用,建立了数学模型,对维修效用进行定量计算.所建立的边际维修理论对于维修经济性的提高和定量计算有一定的指导作用.     

天基信息支援下地基预警雷达搜索空域优化

对天基信息支援下的地基预警雷达搜索空域优化进行了研究。建立了战术弹道导弹（TBM）的运动模型和预警卫星的测量模型,用Unscented卡尔曼滤波（UKF）算法对TBM的运动状态进行滤波估计,并结合解二体运动方程确定搜索空域的中心位置,根据误差传播公式建立了搜索空域半径的确定模型。仿真结果表明：该优化方法符合反TBM预警的实际,可明显提高地基预警雷达对TBM的发现概率。     

空间遥感器大口径反射镜支撑结构型式综述

文章针对空间遥感器大口径反射镜（口径大于500mm）总结了影响支撑结构设计的主要因素，介绍了几种主要的支撑结构型式，并讨论了支撑结构设计中所需要考虑的若干问题。     

神经网络在R＆D项目中止决策中的应用

在比较研究国内外Ｒ＆Ｄ项目中止决策理论方法在基础上，论述了对正在进行的Ｒ＆Ｄ项目进行正确的中止决策模式识别的重要意义。探讨了神经网络（ＮＮ）理论用于Ｒ＆Ｄ项目中止决策的可行性，提出了适用于正在进行的Ｒ＆Ｄ项目的中止决策分析的Ｈｏｐｆｉｅｌｄ神经网络模式识别方法，并用实例验证了方法的有效性。方法的实施较为方便、计算较为简单，结果也令人满意。表明Ｈｏｐｆｉｅｌｄ神经网络模式识别方法在Ｒ＆Ｄ项目中止决策     

Initial design of laboratories for sustainable habitation

An effective and self-sustainable artificial habitat design is essential for human spaceflight and expansion of mankind into orbit or towards other celestial bodies. There are two approaches that need to be implemented in future sustainable habitats: the use of re-cycling technologies in order to gain experience in closed-loop processes and the primary production of resource materials using In Situ Resource Utilisation (ISRU) principles. Various products will be provided and, where applicable, recycled in such a system taking into account basic human factors requirements such as crew work load capacity, safety and well-being, namely:     

统计模式识别方法在高压压气机振动监测中的应用

本文研究了统计模式识别方法在某高压压气机振动监测中的应用，主要涉及了主成分提取算法和距离判别算法。研究结果表明，该方法可以应用到该高压压气机振动监测中去，并且获得了较好的结果。     

基于模糊模式识别的多通道目标选择算法

给出一种多通道用户界面的三维表示模型，证明目标选择是多通道人机交互技术的核心。针对多通道用户界面中输入信息的不精确性，运用模糊模式识别理论，提出根据不精确输入信息进行的目标选择算法。     

一种改进的Dolph—Chebyshev方法在阵列天线方向图综合中的应用

通过对传统Chebyshev多项式增加修正因子得到一种修正的Chebyshev多项式，并以此为基础提出了一种新的阵列天线方向图综合方法。与传统Chebyshev综合法相比，该方法可以在保持副瓣电平不变的情况下对主瓣进行任意展宽，待求参数少，综合过程简单，有很强的实用性。     

Classification of hyperspectral remote-sensing data with primal SVM for small-sized training dataset problem

With recent technological advances in remote sensing, very high-dimensional (hyperspectral) data are available for a better discrimination among different complex land-cover classes having similar spectral signatures. However, this large number of bands makes very complex the task of automatic data analysis. In the real application, it is difficult and expensive for the expert to acquire enough training samples to learn a classifier. This results in a classification problem with small-size training sample set. Recently, a regularization-based algorithm is usually proposed to handle such problem, such as Support Vector Machine (SVM), which usually are implemented in the dual form with Lagrange theory. However, it can be solved directly in primal formulation. In this paper, we introduces an alternative implementation technique for SVM to address the classification problem with small-size training sample set. It has been empirically proven that the effectiveness of the introduced implementation technique which has been evaluated by benchmark datasets.