Fast Probabilistic Particle Identification algorithm using silicon strip detectors

Active detectors used as radiation monitors in space are not usually able to perform Particle Identification (PID). Common techniques need energy loss spectra with high statistics to estimate ion abundances. The ALTEA-space detector system is a set of silicon strip particle telescopes monitoring the radiation environment on board the International Space Station since July 2006 with real-time telemetry capabilities. Its large geometrical factor due to the concurrent use of six detectors permits the acquisition of good energy loss spectra even in a short period of observation. In this paper we present a novel Fast Probabilistic Particle Identification (FPPI) algorithm developed for the ALTEA data analysis in order to perform nuclear identification with low statistics and, with some limitations, also in real time.     

驾驶员诱发振荡的抑制方法

对电传操纵系统驾驶员诱发振荡（ＰＩＯ）的现象进行了分析，指出了舵回路速率饱和是造成ＰＩＯ的主要原因，并有针对对给出了一种非常规的用于解决饱和非线性问题的程序控制方法。这种方法主要是通过舵回路反馈的状态信息来改变驾驶杆输入信号的放大系数，从而达到有效抑制ＰＩＯ的目的，同时用Ｈｕｒｗｉｔｚ稳定判据进行了机理分析，最后给出了仿真验证结果，证明该方法是简单而有效的。     

WL10型近红外反射式光电传感器的研制

依据光学电子学的相关原理，针对烟草行业自动生产过程中对传感器的需要，研制了ＷＬ１０型近红外反射光电传感器，并成功地应用于烟草行业的生产线上。     

PC控制在炼焦项目中的应用

以三菱AnS系列可编程控制器为例，在介绍其主要模块的性能参数基础上，从硬件和软件两方面，阐述了如何实现对拦焦机和装煤车的控制及其控制特点。     

B737飞机座舱增压系统典型间断性故障分析

介绍了第二代B737飞机座舱增压系统后外流活门和加温垫的工作及控制原理,对实际维护中的一种典型故障进行了分析和研究。     

多层模糊逻辑控制器的设计

本文提出一种适合于多输入多输出(MIMO)系统的多层模糊逻辑控制器(MLFLC)，该控制器由若干个多输入单输出(MISO)模糊控制器构成，每个MISO模糊控制器由许多单输入单输出(SISO)模糊控制器组成。该控制器采用互补型隶属函数，具有一组零控制面，只要使量化因子满足一定的条件，控制系统就是渐近稳定的。最后将上述控制器用于二节机械手中进行仿真试验，验证了上述算法的可行性和有效性。     

具有多输入和扰动作用的空空导弹滚动通道的前馈/反馈自适应控制器

中程空空导弹的参数处于激烈、大范围的时变中，采用古典控制器很难满足不同高度弹道的性能规范。为了使导弹在飞行高度和速度大范围变化时均能保持优良性能，采用数字自适应控制方法是合适的。本文提出了一种基于超稳定性理论的飞行控制系统方案，其性能明显优于不采用自适应控制器的古典系统。     

飞机自动着陆纵向块对角控制器设计

在阐述了块对角控制理论和分析飞机运动特性的基础上,把飞机纵向运动方程转化为块对角非线性系统,并设计了飞机自动着陆纵向块对角控制器。仿真结果表明,该控制器能够控制飞机自动着陆,跟踪性能良好。     

Neural adaptive control for a ground experiment of the space proximity operation in a six-degree-of-freedom micro-gravity simulation system

In this study, a neural adaptive controller is developed for a ground experiment with a spacecraft proximity operation. As the water resistance in the experiment is highly nonlinear and can significantly affect the fidelity of the ground experiment, the water resistance must be estimated accurately and compensated using an active force online. For this problem, a novel control algorithm combined with Chebyshev Neural Networks (CNN) and an Active Disturbance Rejection Control (ADRC) is proposed. Specifically, the CNN algorithm is used to estimate the water resistance. The advantage of the CNN estimation is that the coefficients of the approximation can be adaptively changed to minimize the estimation error. Combined with the ADRC algorithm, the total disturbance is compensated in the experiment to improve the fidelity. The dynamic model of the spacecraft proximity maneuver in the experiment is established. The ground experiment of the proximity maneuver that considers an obstacle is provided to verify the efficiency of the proposed controller. The results demonstrate that the proposed method outperforms the pure ADRC method and can achieve close-to-real-time performance for the spacecraft proximity maneuver.     

基于动态补偿的多电机控制算法

多电机协调控制达到转速一致是电机控制中的一个关键难题，外加负载变动和电机参数变化时会引起电机性能的下降，达不到良好的控制效果。为使电机间保持转速同步，建立了永磁同步电机d-q坐标系下的矢量控制数学模型，基于转速跟随控制，提出一种基于单神经元PID的变增益速度补偿器进行偏差耦合控制。在MATLAB/Simulink建立了3台永磁同步电机的仿真模型。仿真结果表明，与传统PID固定增益速度补偿器算法相比，单神经元PID的变增益速度补偿器具有更强的鲁棒性以及更快的收敛性。