Robust wavelet neuro control for linear brushless motors

Design, simulation and experimental implementation of a wavelet basis function network learning controller for linear brushless dc motors (LBDCM) are considered. Stability robustness with position tracking is the primary concern. The proposed controller deals mainly with external disturbances, e.g. nonlinear friction force and payload variation in motion control of linear motors. It consists of two parts, one is a state feedback component, and the other one is a learning feedback component. The state feedback controller is designed on the basis of a simple linear model, and the learning feedback component is a wavelet neural controller. The attenuation effect of wavelet neural networks on friction force is first verified by the numerical method. The learning effect of wavelet neural networks on friction force is also shown in the numerical results. Then, a wavelet neural network is applied on a real LBDCM to on-line suppress the friction force, which may be variable due to the different lubrication. The effectiveness of the proposed control schemes is demonstrated by simulated and experimental results.     

数据库开放对象的数学模型

本文根据系统论提出了开放对象的概念,认为客观世界是由开放对象构成的。它本身是一个递归定义的层次结构,同时具有目的性和适应环境、改造环境的能力即具有自我进化的能力。每个开放对象与其外界的通讯只能通过信息来完成,而且允许它们对同一个消息具有完全不同的理解。开放对象实质是面向对象+人工智能+数据库的一个模型。同时本文还给出它的形式定义。     

Performance analysis of a radar target discrimination technique

The performance of a radar target discrimination technique using multiple-frequency scattering amplitude without phase data is investigated. Based on the concept of natural resonance frequencies, the technique is aspect independent so that a priori information of the aspect angle is not necessary. The radar cross sections (RCSs) of spheroids are calculated numerically to simulate the received radar returns for distinguishing different spheroids and wires in the resonance frequency range by the proposed technique. By Monte Carlo simulation, the discrimination error rate is estimated as a function of the standard deviation of added noise. The numerical results show that the discrimination algorithm works well under moderately noisy situations and can be applied even in a high-resonance frequency range     

某型火箭弹射座椅座高无法调节的故障浅析

本文从弹射座椅无法升降和直流发动机消耗电流过大的现象入手,结合座椅升降系统的工作原理对故障进行分析,最终准确定位故障.对从事飞机座椅调试人员有一定的指导意义.     

低速溅射小行星表面采样的动力学仿真

开发了适用于小行星环境的大规模三维离散元程序DEMBody,针对低速射弹溅射表层风化层的小行星采样方案,仿真了相同质量不同形状的射弹在微重力环境下垂直射入颗粒床的过程,研究了溅射物质在采样器中的运动历程及最终收集质量与射弹形状的关系。结果表明,90°锥形射弹的采样效率最高。     

基于光纤耦合金刚石NV色心系综磁强计的电路诊断方法

为考查应用新型磁强计——金刚石氮空穴(nitrogen-vacancy,NV)色心系综磁强计进行电路诊断的可行性和可靠性,从金刚石NV色心系综磁强计的基本原理出发,搭建了一套光纤耦合金刚石NV色心系综磁强计测试实验系统,将探头紧贴于电路导线外壳,通过测量磁强计处磁场信号的变化实现对电路的诊断.实验结果表明,金刚石NV色...     

宇航矢量伺服控制器在SiP中的设计与实现

磁场导向控制FOC（field-oriented control）矢量控制算法在伺服驱动控制系统中一般由CPU或DSP实现，难以满足航天应用中实时性较高场景下的需求。为提高宇航电机系统控制的实时性与可靠性，从FOC矢量控制算法的硬件加速角度出发，详细介绍了伺服控制器的设计，给出了一种全数字、高性能的伺服控制器硬件加速设计方案，并在具有可编程逻辑功能的宇航级SiP6117S芯片上进行了验证。仿真实验表明，相比于前人的设计，通过调整观测数据的量化精度来降低硬件加速过程中的处理延时，能有效改善多级流水延迟并在一定程度上提升算法的实时性。     

Study of ionospheric D region changes during solar flares using MF radar measurements

During solar flares, the X-ray radiation suddenly increases, resulting in an increase in the electron density of the atmospheric D region and a strong absorption of short-wave radio waves. Based on Langfang medium frequency (MF) radar, this paper analyzed the variation characteristics of D region in the lower ionosphere from 62 km to 82 km. The analysis focused on multiple C-level and M-level solar flare events before and after the large-scale flare event at 11:53 (UT) on September 6, 2017. The results show that it is difficult to detect the electron density over 70 km in Langfang during solar flares, but the electron density value can be obtained as low as 62 km, and the stronger the flare intensity, the lower the detectable electron density height. Besides, the equal electron density height, the received power of X and O waves will also be significantly reduced during the flares, and the reduction of equal electron density height has a weak linear relationship with flare intensity.     

基于时标分解的弹性高超声速飞行器智能控制

考虑弹性高超声速飞行器纵向动力学模型，提出了一种基于时标分解的智能控制方法。考虑刚体状态和弹性模态具有不同的时标特性，采用奇异摄动理论进行快慢时标分解，将模型转换为刚体慢变子系统和弹性快变子系统。针对刚体子系统考虑动力学不确定，基于平行估计模型构造表征不确定逼近效果的预测误差，结合跟踪误差给出复合学习控制策略。针对弹性子系统设计自适应滑模控制稳定弹性模态。通过李雅普诺夫稳定性分析可证系统状态一致终值有界。仿真表明所提出的控制方法能够实现刚弹模态的稳定收敛，且具有更高的跟踪精度、更好的学习性能和更快的收敛速度。