混合遗传算法在航天器最优交会中的应用

推导了航天器双冲量交会时的优化模型,以此为基础构造了最优交会的燃料-时间混合优化指标,并针对基本遗传算法局部搜索能力不强的问题,提出一种将最速下降法与遗传算法相结合的混合遗传算法,其中下降搜索的优化方向利用每一代中最劣个体所包含的优化信息获得。数值计算表明,该混合算法可加速算法的收敛,具有良好的优化性能和函数适应能力。最后,对共面圆轨道双冲量交会情况进行了仿真计算,仿真结果表明混合遗传算法的设计是成功的。     

基于LMI的不确定线性系统观测器设计

研究了不确定线性系统的观测器设计问题。利用凸优化理论将基于线性矩阵不等８式（ ＬＭＩ）的观测器设计转换为鲁棒控制器设计,给出了标准的ＬＭＩ形式。采用该方法的设计过程只需求解三个线性矩阵不等式就可得到鲁棒控制器。在航空发动机控制应用中表明,基于ＬＭＩ的观测器对于具有干扰的系统仍然能保持系统稳定,数值仿真表明控制效果优于文献「１」的结果。     

Applications of tuned mass dampers to improve performance of large space mirrors

In order for future imaging spacecraft to meet higher resolution imaging capability, it will be necessary to build large space telescopes with primary mirror diameters that range from 10 m to 20 m and do so with nanometer surface accuracy. Due to launch vehicle mass and volume constraints, these mirrors have to be deployable and lightweight, such as segmented mirrors using active optics to correct mirror surfaces with closed loop control. As a part of this work, system identification tests revealed that dynamic disturbances inherent in a laboratory environment are significant enough to degrade the optical performance of the telescope. Research was performed at the Naval Postgraduate School to identify the vibration modes most affecting the optical performance and evaluate different techniques to increase damping of those modes. Based on this work, tuned mass dampers (TMDs) were selected because of their simplicity in implementation and effectiveness in targeting specific modes. The selected damping mechanism was an eddy current damper where the damping and frequency of the damper could be easily changed. System identification of segments was performed to derive TMD specifications. Several configurations of the damper were evaluated, including the number and placement of TMDs, damping constant, and targeted structural modes. The final configuration consisted of two dampers located at the edge of each segment and resulted in 80% reduction in vibrations. The WFE for the system without dampers was 1.5 waves, with one TMD the WFE was 0.9 waves, and with two TMDs the WFE was 0.25 waves. This paper provides details of some of the work done in this area and includes theoretical predictions for optimum damping which were experimentally verified on a large aperture segmented system.     

Optimization of geosynchronous satellite constellation for independent regional navigation and positioning in Middle East region

Regional Navigation and positioning systems using geosynchronous satellites are emerging for different parts of the world. Optimal constellation geometry achievement for a set of geosynchronous satellites is a key sector in designing of such systems. Genetic algorithm is applied for optimization of constellations with 6 and 7 satellites which is to be used in Middle East region where these systems have been deprived of. Based on the fact that the coverage criterion is not sufficient enough to guarantee a good navigation service, positioning process by the satellite systems is discussed and the performance of the system on the basis of position dilution of precision is collected as the fitness criterion. Placing the satellites in groups to pass over the same ground track is applied as a constraint to the genetic algorithm. By simulation, performance of the best obtained results and GPS are compared in terms of position dilution of precision, visibility and the required epochs (time span) to resolve the ambiguities with a 99% success rate, in this region. Also, capability of the GA for such problems is demonstrated.     

A residual based adaptive unscented Kalman filter for fault recovery in attitude determination system of microsatellites

This paper presents an adaptive unscented Kalman filter (AUKF) to recover the satellite attitude in a fault detection and diagnosis (FDD) subsystem of microsatellites. The FDD subsystem includes a filter and an estimator with residual generators, hypothesis tests for fault detections and a reference logic table for fault isolations and fault recovery. The recovery process is based on the monitoring of mean and variance values of each attitude sensor behaviors from residual vectors. In the case of normal work, the residual vectors should be in the form of Gaussian white noise with zero mean and fixed variance. When the hypothesis tests for the residual vectors detect something unusual by comparing the mean and variance values with dynamic thresholds, the AUKF with real-time updated measurement noise covariance matrix will be used to recover the sensor faults. The scheme developed in this paper resolves the problem of the heavy and complex calculations during residual generations and therefore the delay in the isolation process is reduced. The numerical simulations for TSUBAME, a demonstration microsatellite of Tokyo Institute of Technology, are conducted and analyzed to demonstrate the working of the AUKF and FDD subsystem.     

采用改进非支配近邻免疫算法的低轨混合星座设计优化

针对低轨同构星座覆盖资源在纬度上分布不均匀的不足,提出采用低轨混合星座提升覆盖均匀性的设计方案,并推导了满足全球任意点平均每天覆盖一定次数的最小卫星规模估算公式。针对非支配近邻免疫算法（NNIA）约束处理方面的不足,提出基于约束支配的改进非支配近邻免疫算法（Modified NNIA）,并以此设计了一种低轨混合星座优化平台来优化带约束的星座设计问题。仿真结果表明,改进的NNIA算法在收敛速度和多样性上均优于非支配分层遗传算法（NSGA II）和多目标粒子群算法（MOPSO）,可大大提高星座设计的效率。同时优化结果也表明低轨混合星座可提高覆盖的均匀性和大部分区域的覆盖次数,进而减少特定覆盖要求所需的卫星数目。     

基于STM32F429的全向运动平台的运动控制

全向运动平台系统是可以实现人体在各个方位行走的2D运动平台。针对实现人体在全向运动平台稳定行走的运动控制,采用加入观测器的一阶控制算法对平台运动控制进行探究。先通过MATLAB软件进行算法的仿真,验证方法的可行性;再通过现场测试,验证控制算法的有效性。最终试验表明,加入观测器的一阶控制算法可对全向运动平台实现有效的运动控制。此运动控制策略的探究为全向运动平台的运动控制提供了一种可行的控制思路和方案。     

Adaptive Gaussian sum squared-root cubature Kalman filter with split-merge scheme for state estimation

The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for improvement of accuracy and consistency. An efficient new algorithm called the adaptive Gaussian-sum square-root cubature Kalman filter（AGSSCKF） with a split-merge scheme is proposed. It is developed based on the squared-root extension of newly introduced cubature Kalman filter（SCKF） and is built within a Gaussian-sum framework. Based on the condition that the probability density functions of process noises and initial state are denoted by a Gaussian sum using optimization method, a bank of SCKF are used as the sub-filters to estimate state of system with the corresponding weights respectively, which is adaptively updated. The new algorithm consists of an adaptive splitting and merging procedure according to a proposed split-decision model based on the nonlinearity degree of measurement. The results of two simulation scenarios（one-dimensional state estimation and bearings-only tracking） show that the proposed filter demonstrates comparable performance to the particle filter with significantly reduced computational cost.     

基于模块度的复杂网络社团结构聚类新算法

针对传统的分裂聚类算法删除连边会影响节点划分的问题,结合K-means算法的思想并加以改进,提出了一种以邻居节点为聚类备选集,所有社团中心节点同时聚类的同步聚类算法。该算法根据节点中心度和最短路变化率确定社团中心节点集,然后以中心节点为社团中心,以邻居节点为聚类备选集合进行聚类,完成社团的划分。将算法应用到Zachary网络中并与GN算法、Top Leader算法进行比较,仿真结果表明该算法对网络有较好的划分。     

DOA estimation and mutual coupling calibration with the SAGE algorithm

In this paper, a novel algorithm is presented for direction of arrival（DOA） estimation and array self-calibration in the presence of unknown mutual coupling. In order to highlight the relationship between the array output and mutual coupling coefficients, we present a novel model of the array output with the unknown mutual coupling coefficients. Based on this model, we use the space alternating generalized expectation-maximization（SAGE） algorithm to jointly estimate the DOA parameters and the mutual coupling coefficients. Unlike many existing counterparts, our method requires neither calibration sources nor initial calibration information. At the same time,our proposed method inherits the characteristics of good convergence and high estimation precision of the SAGE algorithm. By numerical experiments we demonstrate that our proposed method outperforms the existing method for DOA estimation and mutual coupling calibration.