可重复使用航天器时间协同飞行轨迹优化

针对可重复使用航天器(RLV)时间协同飞行轨迹优化问题,提出了一种基于Radau伪谱法的轨迹优化方法。方法以再入飞行时间可知性、可控性为目标,使用Radau伪谱法对RLV的飞行时间进行预测,进而协调出多RLV的再入协同飞行时间,以此再入飞行时间为终端约束使用Radau伪谱法生成满足协同飞行要求的再入轨迹。仿真结果表明,上述轨迹优化方法可以得到满足时间协同约束、状态约束和控制约束的飞行轨迹,具有较高的稳定性和较快的求解速度。所提方法满足多架RLV时间协同再入飞行的需求,具有很强的实用价值。     

基于傅里叶级数的小推力航天器快速轨迹设计

为了满足小推力航天器交会轨迹的快速性设计需求,基于形状逼近理论,设计了一种三维轨迹模型.将轨迹设计问题转换为求解傅里叶级数的系数问题,避免了轨迹运动方程非线性强、难以求解的难题,极大地提高了计算效率.考虑到推力加速度的限制,建立了加速度约束方程,并结合轨迹的运动方程,给出了傅里叶级数的求解过程.同时根据边界条件和最大推力加速度值,定性地分析了傅里叶系数的存在条件.仿真验证了该方法的正确性和可行性,并从计算效率上与高斯伪谱法进行了对比,结果表明本文的方法计算耗时仅为高斯伪谱法的0.67%.     

基于Radau伪谱法的重复使用运载器再入轨迹优化

为了提高数值解法的收敛速度,本文利用Radau伪谱法求解重复使用运载器的再入轨迹优化问题.该方法在一组Legendre-Gauss-Radau点上构造全局Lagrange插值多项式对状态变量和控制变量进行逼近,在动力学方程中状态变量对时间的导数可由插值多项式的导数来近似,故可将动力学方程约束转化为在Legendre-Gauss-Radau点上的代数微分方程约束.因此,可将连续时间的最优控制问题转化为有限维的非线性规划(NLP)问题,之后通过稀疏NLP求解器SNOPT即可对其进行求解.最后的仿真结果显示,通过该方法优化后的再入轨迹成功满足过程约束与边界约束.由于该方法的高效率和高精度特性,可将其应用于轨迹快速优化工程实际问题中.     

基于DCNLP法的重复使用运载器再入轨迹设计

介绍了DCNLP法在可重复使用运载器再人段轨迹优化中的应用.首先以可重复使用运载器为对象,以攻角和倾侧角为控制变量,并考虑严格的终端约束和过程约束,建立了以航程最远作为优化目标的最优控制问题模型.然后采用DCNLP法将最优控制问题转化为一般的非线性规划问题,选取各节点上的状态量和控制量作为优化参数.最后应用matlab...     

基于轨迹控制的改进的直接函数法圆弧插补算法

基于直接函数法的圆弧插补算法能够有效提高插补精度,但是在终点判别时需要对两个轴向的步数进行计算,时间较长.在对长轴终点判别方法进行研究的基础上,提出了一种改进的直接函数法的圆弧插补算法.以每步插补的连续前进轴为长轴,并以在长轴上的插补步数为判断基准,对插补点是否到达终点作出判断.该方法要求不同卦限圆弧对应不同长轴.该算...     

基于改进分段Gauss伪谱法的带推力高超声速 飞行器再入轨迹规划

再入轨迹规划是高超声速飞行器领域的热点问题,已吸引了众多国内外专家的关注. Gauss伪谱法以及分段Gauss伪谱法是解决含有多约束轨迹规划问题的一类有效工具.然而,发动机多次点火熄火导致推力不连续以及点火时刻控制输入的连续性要求是带推力高超声速飞行器再入轨迹优化面临的新挑战.本文将问题简化为多脉冲再入轨迹规划问题,基于改进分段Gauss伪谱法生成满足多条件约束的最优再入轨迹.通过设置分段Gauss伪谱法连续性条件,确保飞行器状态与控制输入在分段点处连续衔接.通过无动力自由再入与带推力再入算例对改进分段Gauss伪谱法进行说明,仿真结果也表明,改进分段Gauss伪谱法可有效求解带推力高超声速飞行器再入轨迹规划.     

基于综合评价指标的航天器反作用轮执行机构配置

本文针对航天器控制系统设计中如何进行执行机构配置这一问题,提出一种基于综合评价指标的航天器反作用轮执行机构配置方法.首先,根据控制系统中执行机构配置的功能需求和硬件需求,确定出满足需求的可行配置方案集.该方案集内的执行机构选择为反作用轮,其安装结构选择为斜装式,安装角是根据控制系统的实际需求并以能耗最小为目标进行确定的.然后,针对确定出的可行配置方案集,以执行机构配置的考量特性为评价指标进行综合评价,确定出可行配置方案集内的最优配置方案.在评价方法中,以最小二乘为工具对主观评价方法和客观评价方法进行优化,以各方案对正负理想方案的贴近度为依据确定出方案的优劣.文章最后,以航天器控制系统设计中的实际执行机构配置需求为例,应用该方法进行配置,结果表明该方法可行和有效,具有工程应用价值.     

民机编队的多阶段轨迹优化

针对编队在民航领域的应用问题,论文提出了一种多阶段轨迹优化模型。首先对编队飞行进行描述,将整个航程划分为起飞爬升段、编队段、进近降落段,与现有航线网络相结合,以具体航路点确保相邻阶段的顺利连接;其次以民机直接运行成本为指标,采用中国民用航空局成本计算方法,确定编队飞机的机型;最后选取时间和燃料消耗为性能指标,建立飞机质心运动方程,设置起降机场、编队航段等约束条件。充分考虑航班各阶段飞行特性和约束,通过数值算例得到两航班编队运行后的最优轨迹,为航班的编队运行提供参考。     

基于6-UCU型平台并联机床的轨迹时间优化

本文针对基于6-UCU型Stewart平台的并联机床提出了一种轨迹时间优化方法。建立该运动平台的运动学逆解模型。通过三次多项式插值对上平台的轨迹点进行插值,通过反解模型求出各个驱动臂对应的位移。建立时间优化的模型,使用遗传算法结合五次多项式插值对轨迹点之间的速度,加速度进行求解。计算得出优化后的运行时间与未优化前对比优化了14.9%。最后将得到的加速度导入到ADMAS模型中进行仿真验证,结果表明该轨迹运行平稳,仿真测量的驱动臂位移与计算得出无明显差别。     

航天器多维动态可配置健康管理系统设计

以工程任务为牵引,提出了一种基于多维动态可配置模型的航天自主健康管理及控制系统设计与实现方法,有效解决了不同航天器间自主控制管理需求差异大、开发效率低等问题,具有一定的创新性。阐述了系统的设计思路,并给出实现示例,通过参数的动态表格化配置、判据的多源拟合等设计,实现健康管理规则库的构建;通过数据有效性服务的设计,完成对航天器健康状态判断数据源的质量控制;无差别异常检测模块、异常隔离与恢复等模块的设计,保障了航天器异常状态的实时处置,确保航天器安全运行。通用化的模型设计可支持不同航天器的自主健康管理及控制系统,已获得多个型号整器级测试应用验证,具有推广价值。     

Direct Trajectory Optimization and Costate Estimation of Infinite-horizon Optimal Control Problems Using Collocation at the Flipped Legendre-Gauss-Radau Points

A pseudospectral method is presented for direct trajectory optimization and costate estimation of infinite-horizon optimal control problems using global collocation at flipped Legendre-Gauss-Radau points which include the end point +1. A distinctive feature of the method is that it uses a new smooth, strictly monotonically decreasing transformation to map the scaled left half-open interval τ∈(-1, +1] to the descending time interval t ∈ (+∞, 0]. As a result, the singularity of collocation at point +1 associated with the commonly used transformation, which maps the scaled right half-open interval τ∈[-1, +1) to the increasing time interval [0,+∞), is avoided. The costate and constraint multiplier estimates for the proposed method are rigorously derived by comparing the discretized necessary optimality conditions of a finite-horizon optimal control problem with the Karush-Kuhn-Tucker conditions of the resulting nonlinear programming problem from collocation. Another key feature of the proposed method is that it provides highly accurate approximation to the state and costate on the entire horizon, including approximation at t = +∞, with good numerical stability. Numerical results show that the method presented in this paper leads to the ability to determine highly accurate solutions to infinite-horizon optimal control problems.      

Two Direct Low Thrust Trajectory Optimization Techniques

Journal of Computer and Systems Sciences International - Direct low thrust trajectory optimization techniques that reduce the optimization problem in the class of continuous functions to a...     

Reentry Trajectory Optimization for Hypersonic Vehicles Using Fuzzy Satisfactory Goal Programming Method

Constrained reentry trajectory optimization for hypersonic vehicles is a challenging job. In particular, this problem becomes more difficult when several objectives with preemptive priorities are expected for different purposes. In this paper, a fuzzy satisfactory goal programming method is proposed to solve the multi-objective reentry trajectory optimization problem. Firstly, direct collocation approach is used to discretize the reentry trajectory optimal-control problem with nonlinear constraints into nonlinear multiobjective programming problem with preemptive priorities, where attack angles and bank angles at nodes and collocation nodes are selected as control variables. Secondly, the preemptive priorities are transformed into the relaxed order of satisfactory degrees according to the principle that the objective with higher priority has higher satisfactory degree. Then the fuzzy satisfactory goal programming model is proposed. The balance between optimization and priorities is realized by regulating parameter λ, such that the satisfactory reentry trajectory can be acquired. The simulation demonstrates that the proposed method is effective for the multi-objective reentry trajectory optimization of hypersonic vehicles.     

Collocation Dictionary Optimization Using WordNet and k-Nearest Neighbor Learning

In machine translation, collocation dictionaries are important for selecting accurate target words. However, if the dictionary size is too large it can decrease the efficiency of translation. This paper presents a method to develop a compact collocation dictionary for transitive verb–object pairs in English–Korean machine translation without losing translation accuracy. We use WordNet to calculate the semantic distance between words, and k-nearestneighbor learning to select the translations. The entries in the dictionary are minimized to balance the trade-off between translation accuracy and time. We have performed several experiments on a selected set of verbs extracted from a raw corpus of over 3 million words. The results show that in real-time translation environments the size of a collocation dictionary can be reduced up to 40% of its original size without significant decrease in its accuracy.     

基于VAE-DBN双模型的智能文本分类方法

文本分类技术是信息过滤、搜索引擎等领域的基础,是当下研究热点之一。本文在介绍文本分类相关概念、深度学习相关模型的基础上,通过分析传统文本分类方法存在的不足,提出基于变分自编码器模型和深度置信网络模型（VAE-DBN）的双模型融合的文本分类方法。通过在相关语料集上的对比验证,表明该双模型方法能有效提高文本分类的准确性。     

A Fast and Unified Method to Find a Minimum-Jerk Robot Joint Trajectory Using Particle Swarm Optimization

In robot trajectory planning, finding the minimum-jerk joint trajectory is a crucial issue in robotics because most robots are asked to perform a smooth trajectory. Jerk, the third derivative of joint position of a trajectory, influences how smoothly and efficiently a robot moves. Thus, the minimum-jerk joint trajectory makes the robot control algorithm simple and robust. To find the minimum-jerk joint trajectory, it has been formulated as an optimization problem constrained by joint inter-knot parameters including initial joint displacement and velocity, intermediate joint displacement, and final joint displacement and velocity. In this paper, we propose a fast and unified approach based on particle swarm optimization (PSO) with K-means clustering to solve the near-optimal solution of a minimum-jerk joint trajectory. This work differs from previous work in its fast computation and unified methodology. Computer simulations were conducted and showed the competent performance of our approach on a six degree-of-freedom robot manipulator.     

基于非参数密度估计的不确定轨迹预测方法

随着大量移动设备的出现,准确和高效的轨迹预测有助于提高面向位置的应用和服务的质量和水平.针对现有方法对轨迹不确定性缺乏有效建模的问题,提出了基于非参数密度估计的不确定轨迹终点预测方法.在轨迹建模及模型训练阶段,利用非参数估计对起点与终点相同的轨迹构建基于密度分布的不确定轨迹模型;在轨迹预测阶段,将待预测轨迹视为轨迹数据流,并通过KS（Kolmogorov-Smirnov）检验方法与具有相同起点的不确定轨迹模型进行匹配,其中匹配程度最高的不确定轨迹即为预测轨迹.通过真实轨迹数据集上的实验表明,与现有各类主要轨迹预测方法相比,本方法在不同条件下的预测效率与准确性都有较明显优势.     

一种直接基于摆角约束的欠驱动桥式吊车轨迹规划方法

针对非线性桥式吊车系统,本文提出了一种新颖的基于摆角约束的轨迹规划方法.为了提高运送过程的效率和安全性,论文设计了期望轨迹以实现如下优点: 1)使台车很快到达目标位置; 2)将负载摆角抑制到可接受的范围之内; 3)当负载在目标位置停止时无残余摆动.具体而言,所设计的轨迹由三个阶段构成,每一阶段均根据抗摆和零残余摆角的要求来构造摆角曲线,在此基础上,利用桥式吊车的非线性运动学方程分析得到台车轨迹.论文引入了一种优化机制对运送时间,最大摆角等指标进行折衷考虑.文中通过仿真和实验结果表明了所设计的直接基于摆角约束的轨迹规划方法的性能.     

混合遗传算法求解高超音速飞行器弹道优化

高超音速巡航导弹最优上升轨道设计问题是终端时刻未定、终端约束苛刻的最优控制问题,经典算法求解这类问题时对初值选取敏感、局部收敛等问题表现得比较突出.针对上述问题,将具有良好全局收敛性的遗传算法应用到导弹最优上升段设计问题求解中,为了提高遗传算法的收敛速度和克服早熟问题,结合单纯形和Powell算法的优点,设计了两种混合遗传算法.通过所设计的两种混合遗传算法的求解结果和分别用单纯形以及Powell算法的求解结果进行比较,得出所设计的混合遗传算法是更有效的求解高超声速巡航导弹轨迹优化的方法.