考虑黏弹性材料随机性的被动约束层阻尼梁动力学分析

采用传递函数方法研究了阻尼层黏弹性材料随机性对被动约束层阻尼(PCLD)梁动力学特性的影响。由Hamilton原理建立了PCLD梁六阶运动微分方程,通过引入状态向量,建立了系统的状态空间方程,利用传递函数方法得到了梁的固有频率和损耗因子。以黏弹性材料分数导数模型中的参数作为基本的随机变量,并假设其服从正态分布,使用Monte Carlo直接抽样法考察了材料模型参数的随机性对结构固有频率和模态损耗因子的影响。计算结果表明黏弹性材料参数的随机性对梁动力学特性的变异系数影响较大,模态损耗因子的变异系数最大值是材料参数变异系数的4.5倍。     

机械抖动偏频激光陀螺静态测角方法

阐述采用机械抖动偏频激光陀螺进行静态角度测量的原理,分析测角随机误差与激光陀螺角随机游走系数、测量时间的关系,通过转台分度误差实验验证了测角随机误差公式。采用排列互比法对测角系统误差和转台分度误差进行分离。实验与理论分析表明,静态测角方法具有良好的环境适应性和稳定性,测角随机误差优于0.26″,系统误差优于1″。最后分析了进一步减小测角随机误差和系统误差的措施。     

Adaptive random search for continuous simulation optimization

We present, analyze, and compare three random search methods for solving stochastic optimization problems with uncountable feasible regions. Our adaptive search with resampling (ASR) approach is a framework for designing provably convergent algorithms that are adaptive and may consequently involve local search. The deterministic and stochastic shrinking ball (DSB and SSB) approaches are also convergent, but they are based on pure random search with the only difference being the estimator of the optimal solution [the DSB method was originally proposed and analyzed by Baumert and Smith]. The three methods use different techniques to reduce the effects of noise in the estimated objective function values. Our ASR method achieves this goal through resampling of already sampled points, whereas the DSB and SSB approaches address it by averaging observations in balls that shrink with time. We present conditions under which the three methods are convergent, both in probability and almost surely, and provide a limited computational study aimed at comparing the methods. Although further investigation is needed, our numerical results suggest that the ASR approach is promising, especially for difficult problems where the probability of identifying good solutions using pure random search is small. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Averaging frameworks for simulation optimization with applications to simulated annealing

We present two frameworks for designing random search methods for discrete simulation optimization. One of our frameworks is very broad (in that it includes many random search methods), whereas the other one considers a special class of random search methods called point‐based methods, that move iteratively between points within the feasible region. Our frameworks involve averaging, in that all decisions that require estimates of the objective function values at various feasible solutions are based on the averages of all observations collected at these solutions so far. Also, the methods are adaptive in that they can use information gathered in previous iterations to decide how simulation effort is expended in the current iteration. We show that the methods within our frameworks are almost surely globally convergent under mild conditions. Thus, the generality of our frameworks and associated convergence guarantees makes the frameworks useful to algorithm developers wishing to design efficient and rigorous procedures for simulation optimization. We also present two variants of the simulated annealing (SA) algorithm and provide their convergence analysis as example application of our point‐based framework. Finally, we provide numerical results that demonstrate the empirical effectiveness of averaging and adaptivity in the context of SA. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

一种基于MMMA的双模式变步长盲均衡算法

针对传统修正恒模算法(MCMA)收敛速度慢、剩余码间干扰大的缺点,在双模式修正恒模算法(MCMA+DD-LMS)的基础上引入局部信息量和变步长的思想,提出了一种基于修正多模算法(MMMA)的双模式变步长修正多模算法(VS-MMMA+DD-LMS)。经过理论分析和实验仿真,证明改进后的算法较传统算法具有更好的均衡效果。     

模糊离散变结构控制系统研究

系统研究了模糊离散变结构控制的设计方法,提出了几种具体设计方案.对于变结构控制而言,模糊逻辑的引入可以使滑模(变结构)控制具备推理和学习能力,控制信号得以柔化,能够减轻或避免一般滑模控制的抖振现象;对于模糊控制而言,滑模控制思想的引入可以大大简化控制结构,保证控制系统的鲁棒稳定性,对模糊控制系统的设计和性能分析提供了一种工具.     

模糊识别和随机森林算法在柴油机振动信号状态识别中的应用

针对模糊识别算法中,样本特征向量中各参量(分量)对状态分类的贡献权重难以确定的问题,提出了利用随机森林算法对特征参量的重要度评估结果作为特征权重的方法。通过对柴油机台架试验振动信号的跟踪分析,获得了柴油机在磨合期、100摩托小时、200摩托小时、300摩托小时及400摩托小时5种不同使用期(典型状态)的75个振动信号样本,然后计算出各类样本在幅域、时域和频域的特征参量,利用随机森林算法进行特征选择,确定4个重要特征参量及其权重,用统计方法得出其隶属度函数,最后根据评价向量对样本进行识别,识别准确率达到94%以上。     

像管电子光学系统多目标优化的研究

将多重网格法用于静电像管电子光学场分布计算,采用改进的约束变尺度法进行静电聚焦像管的优化设计,较大地提高了电场分布的计算精度和像管设计效率,减少了计算时间和设计周期。研究的加权最小二乘法构造优化计算的多目标函数,普遍适用于调焦、定焦、变倍、选通和校畸变等各种类型静电像管的设计与计算。     

基于随机集理论的多目标跟踪方法

多目标跟踪问题通常包括目标信号的检测与目标状态的估计,同时还涉及到对探测范围内目标数量的确定。传统的跟踪方法将目标检测、状态估计与数量确定分别使用独立的模块或算法来处理。在这种模式下,每个模块仅考虑测量数据中与其功能直接相关的信息,模块之间没有信息的交互,因而很难得到全局最优的解。基于随机集理论的多目标跟踪方法将场景内的全部目标看作一个全局变量,目标状态与目标测量分别构成各自的随机有限集。从而多目标跟踪问题可以放在一个随机集模型下的贝叶斯滤波框架中研究。在每一个滤波周期内,通过对随机集的处理,实时地估计目标的数量、状态与类型,实现多目标的联合检测、跟踪与识别。     

改进幂指数趋近律的航空发动机模糊滑模控制

针对滑模变结构控制趋近运动不具有鲁棒性的问题,提出了一种基于改进幂指数趋近律的航空发动机模糊滑模控制策略。采用一种参数模糊自调节的时变滑模面,"主动迎上"系统状态轨迹,而不是被动等待系统状态轨迹落在滑模面上,缩短趋近运动时间,提高控制器的鲁棒性;并提出了一种改进的幂指数趋近律,进一步削弱抖振。仿真结果表明,所设计的控制器取得了令人满意的控制效果,能有效地抑制干扰和参数不确定性的影响,削弱抖振。