基于传感器的6-DOF并联机构运动学正解

6-DOF (Degrees of Freedom)并联机构的位姿正解问题复杂而且多解.讨论了处理正解问题的各种不同方法,其中数值迭代法和使用附加传感器的两种方法可以直接找到正解.重点研究了使用附加传感器获取并联机构正解的方法及传感器的类型,并对采用直线位移传感器和旋转传感器及其配置方法进行了比较,不同的配置会影响到正解的计算精度与计算过程.讨论了采用直线位移传感器与旋转传感器联合求解时合理的传感器数量及相应的配置,并针对一种相对通用的配置方法,推导了获得位姿正解的计算过程. 根据计算分析,采用4个旋转传感器或者3个直线传感器,经过适当的配置,可以获得并联机构的正解.     

6-3 Stewart平台位置正解的机构简化数值方法

针对提高Stewart平台运动学位置正解速度的问题,分析了传统基于速度雅可比的数值迭代方法,并对6-3 Stewart平台结构提出了一种基于机构简化的位置正解数值方法.将6-3 Stewart平台等效为虚拟3-RPS并联机构,通过牛顿-拉夫逊方法对其进行位置正解,并将结果解算为实际机构上平台位姿.设计了一套液压6-3 Stewart平台实验系统,并通过实验证明,与传统方法相比,该方法能减少近50%的迭代次数和约85%的解算时间.该方法概念清晰,机构等效计算简单,对3-RPS并联机构的位置正解计算量明显减少,在目前主流工控机处理器上可满足控制周期0.1 ms实时控制的位置解算需求.     

Stewart台体并联机器人位置正解

为获得Stewart台体并联机器人位置正解的解析解,使用分次字典序Groebner基和Sylvester结式相结合的代数方法对该问题进行研究.利用计算代数中的分次字典序Groebner基算法,计算该机器人位置正解封闭数学模型的分次字典序Groebner基;从得出的51个基中选取20个基,构造20阶Sylvester结式,分析符号形式方程组的变量次数,可以直接得出该机器人位置正解一元高次方程的次数为40且最多有40组解的结论,其结果与前人的完全一致,但结式的尺寸却小得多.为了对结果进行验证,使用同伦连续法对同一个数字算例进行计算,两种方法得到结果一致.为并联机构位置正解的研究提供了一种新的有效算法.     

一种六杆并联机器人的控制问题和控制器研究

针对一种六杆并联结构工业机器人,研究了其运动学逆解和正解算法,以及它们在开放式数控系统中的具体实现技术,解决了基于逆解算法的实时坐标变换问题和基于正解算法的系统初始化问题,并给出了相应模块与数控系统内核的接口,最后在一种开放式数控系统平台上实际开发成功针对这种并联结构机器人的控制系统,从而得出结论,采用正确的实现技术,并联结构机器人的实时控制问题可以在开放式数控系统中很好地得到解决.      

月尘/月壤环境效应地面模拟方法研究

月壤/月尘会附着并污染航天器、月球车的表面,如果不及时清除,还会进一步诱发部件过热、机械机构卡死、密封失效、材料磨损等一系列问题.本文综述了关于月尘特性、月尘与航天器系统的互相作用机理、月尘环境模拟方法等方面的研究成果,提出了一种小型月尘环境模拟系统的设计方案.该系统将使关于月尘特性的实验研究成为可能,并可作为登月飞船及月球车材料选择、机械机构可靠性试验、除尘策略试验的平台.      

判断二次系统存在两个极限环的问题

利用文献[(?)]所述的方法,本文研究了二次系统存在两个极限环的问题。给出了上述问题的全部引理,并在此基础上示范性地给出了该问题的有关定理。     

中心对称平面三连杆的同步运动

研究中心对称平面三连杆的运动.该模型是常见的力学系统,可以近似描述外层空间中弱引力条件下带有太阳能板的卫星的运动状况.然而,由于该系统是不可积系统,一般的运动状况比较复杂.在本文中对该模型建立Lagrange运动方程,主要研究其同步运动,求出同步运动的精确解,并分析其运动规律,证明了在一定条件下存在周期解.本文的结果为进一步研究该系统的在同步运动附近的复杂性打下了基础.      

吴方法在平面并联机构位置正解中的应用

采用吴方法对平面并联机构位置正解问题进行了研究.吴方法是一种求解非线性方程组的数学机械化方法,采用这种方法任何非线性方程组都可以在有限步内得到解决.在给出了吴方法基本原理的基础上,对本问题进行了求解,并将原始方程组转化成为一个三角化的方程组.其中单变量方程的次数为6次,说明平面并联机构可以有6个不同的位姿.最后用数值实例进行了验证,给出了计算结果.吴方法在这一问题中的应用,为求解其它机构学难题提供了新途径.     

基于结构随机跳变系统的反干扰信息处理方法

为了解决在复杂的干扰对抗环境中提高信息处理的准确性问题(例如,对具有多种干扰对抗手段的机动目标的跟踪问题),基于结构随机跳变系统理论提出了一种反干扰信息处理的新方法,该方法针对干扰环境的随机剧烈变化,适时地辨识干扰环境的当前状态,并作出相应的决策来优化和利用系统的资源(例如传感器的优化重组、信息融合算法的转换等),最大限度地降低干扰对信息处理精度的影响.以有效地提高信息优化处理的精确度.在本文中就该方法的性能与其它算法做了仿真比较,其仿真结果证实了该方法的有效性.      

基于G1-变异系数-KL改进TOPSIS雷达对抗干扰有效性评估

干扰效能评估作为多属性决策问题时，为解决传统的逼近理想解排序法（TOPSIS）在进行雷达对抗效能评估时过于客观而不能充分体现评估者意志，并且在使用过程中仅考虑指标间欧氏距离导致某些处于正负理想解中垂线上的点无法分辨的问题，提出一种G1-变异系数-KL改进TOPSIS雷达对抗干扰有效性评估算法。该算法利用G1法和变异系数法分别求得主观和客观权重，并引入差异系数的概念充分反映主客观程度，利用相对熵解决位于正负理想解中垂线上的点无法排序的问题。通过仿真实验可以发现，提出的算法在评价干扰有效性时性能优于传统算法。      

Feasible angular momentum of spacecraft installed with control moment gyros

In this paper, a fundamental approach to analyzing the maneuverability of spacecraft with mounted control moment gyros is addressed by searching feasible angular momentum. The geometrical array of control moment gyros considered is a roof array also known as a 2-SPEED system. Due to the simplicity of the singularity envelope of the array considered, it is reasonably practical to conduct rotational performance analysis of the spacecraft. This maneuverability analysis technique uses a unique chart developed in this work, which allows a guaranteed maximum torque output and angular momentum at any time without concern about the singularity problem of the control moment gyros. Therefore, the purpose of this paper is to provide a conservative method for maneuverability analysis of a spacecraft with installed control moment gyros by searching allowable maximum angular momentum. This method is demonstrated using an illustrative example.     

A new algorithm on increasing the sensitivity of microwave radiometer based on nonlinear prediction

Currently, microwave radiometer, which has been one of the most important remote sensors in the land, ocean or atmosphere remote sensing, has played a vital role in space exploration such as the lunar exploration in China. As a passive remote sensor, microwave radiometer receives the noise resembling signals that are generated by microwave radiation while mixed with the systemic noise of the receiver. Therefore, it is the significant subject that how to improve the sensitivity of microwave radiometer that people devotes to study. And on the system noise reduction lies the key. So far, except through choosing low noise element to the receiver, there is no effective alternative to remove the influence of the systemic noise on output uncertainty of microwave radiometer. However, for the purpose of providing or inspiring solution to this problem, this paper inquires into the application of nonlinear predictive method in predication the systemic noise of microwave radiometer. As the substance of the method, neural network shows its function on reducing the systemic noise effectively by estimating and predicating it. Because neural network can improve the estimated precision when estimating the systemic noise, after the noise passes through filter, certain random characters are lost while determinacy are presented to some extent. In fact, the more narrow filter band is, the smaller predictive error will be. The results are of assistance in understanding the intrinsic quality of the systemic noise and offer a new way for improving property of microwave radiometer.     

一种求非线性规划全局最小解的算法

在评述了近２０年来发展的全局最优化方法之后，提出了一种求解全局最优化问题的算法，即从一个求得的局部最小解点出发，去解一个最大化问题，这个最大化问题是构造一个辅助函数去寻求一个更好的局部最优解，这样就产生一个局部最小解序列，得后得到全局最小解，另外还有了全局收敛性定理，也给出了数值例子。     

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.     

刚弹耦合动力学初值问题拟变分原理及其应用

刚弹耦合动力学在国防和民用经济建设中有着广阔的应用前景,但目前还没有完全成熟的理论研究成果。鉴于此,针对刚弹耦合特性,建立初值问题拟变分原理;应用变分方法,推导拟变分原理的拟驻值条件,即得到刚弹耦合动力学的控制方程;给出刚弹耦合动力学初值问题拟变分原理应用的2个算例,1个是应用控制方程求得自由梁的奇数阶振型的解析解,1个是应用变分直接方法 Ritz方法求得自由梁的偶数阶振型的解析解。研究表明,刚弹耦合动力学初值问题拟变分原理为建立有限元计算模型提供了依据。     

BANK编译模式在扩大单片机程序存储空间中的应用

利用C51编译器的BANK编译模式解决MCS-51系列单片机程序存储空间受64KB限制的问题,分析Keil C51编译器在BANK编译模式下的切换过程,提供一种软硬件的设计方法,并对设计的正确性进行了验证,从而解决了航天器设备典型单片机只能提供16B地址线对程序代码寻址的问题.     

基于SVC视频流的低复杂度多播组分解算法

多播是一种高效率利用带宽资源的技术，可以有效缓解多媒体传输过程中的带宽压力，但传统的多播技术会带来“瓶颈用户”问题，限制多播组内用户的数据速率。多播组分解技术将多播组划分为若干子组并以不同速率接收数据，可以有效解决瓶颈用户带来的速率限制。构建了面向用户端的视频多播传输方案，将可伸缩视频编码（SVC）的分层特点和组分解技术相结合，各多播子组根据实际接收能力解调得到不同质量的SVC视频数据，在保证用户基本视频数据传输的基础上，实现总系统速率最大化。提出了面向资源公平调配的低复杂度多播组分解算法，在改进低复杂度分组（LCS）算法过程中考虑SVC视频层限制，并引入常值向量抑制资源分配不公的情况。经过实验数据模拟和性能评估，所提算法在带宽资源和用户数量变化时，均可以稳定地保持较高的系统速率、频谱效率及系统公平性，且计算复杂度较低，能够实际应用于4G和5G网络架构下的视频传输。      

升力体飞行器能量近似最优倾斜转弯飞行策略

升力体飞行器返回地球大气层内时受到热流、动压及过载等约束条件,为使得飞行器在倾斜转弯飞行过程中能量损失最小,需要研究一种能量最优的倾斜转弯机动飞行策略。本文的主要研究内容包括:从再入动力学模型出发,分析了升力体飞行器倾斜转弯的弹道特性,推导了终端速度与倾斜转弯幅度相关的解析解,提出了一种多约束条件下能量近似最优的倾斜转弯飞行策略;为进一步验证飞行策略的能量近似最优性,建立了能量最优的非线性轨迹优化模型,通过高斯伪谱法进行求解,获得能量最优的飞行轨迹。仿真结果表明,该飞行策略与优化方法获得的结果高度一致,并且该方法求解效率更高,工程应用性更强。      

Finite-time asteroid hovering via multiple-overlapping-horizon multiple-model predictive control

This paper investigates the asteroid hovering problem using the Multiple-Overlapping-Horizon Multiple-Model Predictive Control method. The effectiveness of the predictive controllers in satisfying control constraints and minimizing the required control effort is making Model Predictive Control a desirable control method for asteroid exploration missions which consist of the asteroid hovering phase. However, the computational burden of Model Predictive Control is an obstacle to employing the asteroid’s complex gravitational field model. As an alternative option, the Multiple Horizon Multiple-Model Predictive Control method has been introduced previously, which could provide a solution with the less computational burden with respect to the nonlinear Model Predictive Control. It was shown that it is not necessary to deduce the exact dynamics model to predict the system’s behavior during a long period using this approach. However, the calculated control acceleration was not smooth enough because of the crisp borders of consecutive horizons, which may cause an image motion and degrades the geometric accuracy of high-resolution images in asteroid hovering missions. In this paper, the Multiple-Overlapping-Horizon Multiple-Model Predictive Control method is introduced instead to solve the problem of controlling acceleration fluctuations by overlapping consecutive horizons. Numerical simulation results are presented to validate the effectiveness of the proposed control method, and its advantage is demonstrated accordingly for the asteroid hovering problem in achieving the hovering position and velocity.