某无人机SAR天线系统的热设计

为解决某无人机SAR安装平台无环控、天线系统发热量大、安装空间狭小等问题,文中将热管技术引入机载雷达天线系统的热设计。针对雷达工作状态,分别提出天线系统的挂飞散热方案和地面调试散热方案,并通过地面试验和仿真分析验证散热方案的合理性。结果表明,根据雷达工作状态进行热设计的思路可行,散热方案合理,满足热设计要求。     

牛顿混沌迭代方法及四杆导引机构综合应用举例

机构学问题的数学模型常可化为多元非线性方程组，一般求解多元非线性方程组需要初始值，而初始值的选择是相当困难的。同伦方法不需初始值就能求出全部解，为求解这一问题提供了可行的方法，但需要培写专用的程序，且计算量比较大。该文结合MATLAB7．1高级程序设计语言采用简单的牛顿迭代法迭代，并将非线性方程视为非线性的动力学系统，利用使得系统产生混沌的Julia集的点求解方程的全实数解，而Julia集的点集用二周期逆像函数求得，再在其邻城内求解即可。运用该算法培写了MATLAB程序，并以平面四杆刚体导引机构综合问题为例进行了运算，找到了实现最大精确点时该问题的全部解，为实际机构的设计提供了多种选择方案，为机构学设计提供了一种迭代新算法。     

Estimation of region of attraction for polynomial nonlinear systems: A numerical method

This paper introduces a numerical method to estimate the region of attraction for polynomial nonlinear systems using sum of squares programming. This method computes a local Lyapunov function and an invariant set around a locally asymptotically stable equilibrium point. The invariant set is an estimation of the region of attraction for the equilibrium point. In order to enlarge the estimation, a subset of the invariant set defined by a shape factor is enlarged by solving a sum of squares optimization problem. In this paper, a new algorithm is proposed to select the shape factor based on the linearized dynamic model of the system. The shape factor is updated in each iteration using the computed local Lyapunov function from the previous iteration. The efficiency of the proposed method is shown by a few numerical examples.     

一种LED光源矩形斑照明的优化算法及其仿真

微分方程求解法是设计自由曲面最常用的一种方法之一,此方法是通过建立照明源与被照明面之间的几何关系,来实现自由曲面的数值求解。通常会基于照明光源的光分布与被照明面的照明要求,建立一组偏微分方程,方程组的未知数为自由曲面的每一个节点的坐标和曲率值。通过能量守恒原理,解出所需要的自由曲面每个节点的具体坐标值。在现有微分方程理论的基础上,通过分割自由曲面和变步长的龙格-库塔算法,大幅改善了矩形照明斑的形状、能量利用率及均匀性等,对矩形照明斑质量实现了优化。     

某机载雷达天线框架结构的有限元分析

天线框架是天线的安装平台和精度基准,其结构刚度与强度直接关系到机载雷达的性能。文中以某机载雷达天线框架结构为研究对象,建立了完整的有限元仿真模型,进行了模态分析,给出了结构的前6 阶固有频率及振型,完成了该结构在加速度过载下的准静态分析及随机振动的响应分析,得到了相应的变形和应力值,并计算了相应的安全裕度。结果表明,该机载雷达天线框架具有较高的基频和较好的刚强度,结构设计满足机载产品抗力学环境设计要求。     

Correction factors for films resistivity measurement

The formulation of the correction factor for resistivity measurement using four-point probe has been reviewed. Generally, the typical concern in nanotechnology is the decreasing size and thickness of sample under study as well as the challenge faced in getting a correction factor value of resistivity in four-point probe technique. In this paper, an accurate calculation algorithm is presented to calculate the correction factor for arbitrary configuration of four-point probe method based on a generalized formalism using Laplace’s equation. The computed values of correction function are found to achieve precision of maximum fractional errors below 10⁻¹⁶ with numbers of summation terms less than 100. The general correction factor formulae can be applied to the measured resistivity of the sample grown on insulating or on conducting substrates using linear or non-linear four-point probe. The values of the correction factors are presented in the form of log-log graphs for handy references.     

平面曲柄滑块机构函数综合的混沌方法

采用简单的牛顿迭代法迭代，并将非线性方程视为非线性的动力学系统，利用使得系统产生混沌的Julia集的点，求解方程的全部实数解。而Julia集的点在Jocobi矩阵行列式值为零的解集的邻域内，给定矩阵的行列式值的表达式的一些变量为已知，仅只有一个变量未知，把它转化为一元非线性方程，进而求出其全部解。再确定未给定变量的搜索范围，运用粗、精选代在其邻域内求解即可。运用该算法编写了MATLABB程序，对平面曲柄滑块机构的函数综合问题进行了研究，得出了Jocobi矩阵的通用表达式，从而找到了实现最大精确点时该问题的全部解，为实际的平面曲柄滑块机构的设计提供了多种选择方案，为机构学设计提供了全新的方法。     

基于免疫算法的并行机间歇过程模糊生产调度

研究了一类具有顺序无关模糊产品切换时间和成本以及模糊单位加工时间和成本的并行机间歇过程调度问题,目的是确定每种产品在每个设备上处理的批次数目、批量以及批次顺序,优化目标为最小化总完成时间和最小化总生产成本。根据任意设备上同种产品的所有批次均顺序处理的性质,建立了问题的模糊运输模型。利用加权和方法将多目标函数转化为单目标函数,并使用基于积分值的方法对模糊数进行排序。提出了基于排列边集编码的免疫算法,通过求解不同规模的问题实例证明,免疫算法不仅能获得比遗传算法和免疫遗传算法更好的解,而且比免疫遗传算法更高效,同时具有良好的动态性能。     

某机载SAR天线布局研究

机载SAR天线及转台结构设计中很关键的一点就是天线布局方案的设计.由于天线罩的包络空间有限并且不规则,使得天线布局方案设计复杂,不易优化.针对某机载SAR系统给出了三种天线布局设计方案,并使用Inventor软件的驱动约束功能对天线布局方案进行了简单有效的运动仿真分析,给出了优化设计建议.布局方案及设计方法可以为同类机载SAR天线布局方案设计提供参考.     

基于Lévy飞行微粒群算法的液压系统可靠性优化

针对微粒群算法易于陷入局部最优解、早熟的缺点,将Lévy飞行引入微粒速度迭代公式中,并动态改变微粒群速度迭代公式中Lévy飞行的权重值,提出动态Lévy飞行微粒群算法。根据T-S故障树理论,建立液压支架液压系统的可靠性模型,进而得出可靠性费用目标函数。将提出的动态Lévy飞行微粒群算法应用于液压支架液压系统的可靠性优化中,并通过标准微粒群算法、布谷鸟搜索算法和基于Lévy飞行微粒群算法比较,验证所提出算法的优越性。     

劣化系统的最佳检测与维修周期分析

提出了一类基于半马氏决策过程的劣化失效系统检测与维修优化模型.将位相型(PH)分布引入模型后,决策过程的状态空间发生变化,为了获得适用于原有模型假设的检测与维修优化策略,提出了一种改进的值迭代算法.运用该算法,求得了使系统长期运行平均费用率最低的预防性维修阈值与检测间隔分布.最后,通过具体算例验证了模型与迭代算法的可行性.     

Two heads are better than one: an AIS- and TS-based hybrid strategy for job shop scheduling problems

Job shop problems (JSPs) widely exist in many fields and are usually very hard to solve. Despite the fact that many scheduling algorithms have been studied, it is still challenging to find optimal solutions for certain JSPs. Some studies have shown that it is difficult to solve these JSPs by only using a single search technique, while the hybrid of different ones is usually more effective. In this paper, a hybrid algorithm combining artificial immune system (AIS) with tabu search (TS) is proposed. The AIS is based on the clonal selection principle of biological immune systems and is used to find the solution space with potential high evaluation values. The TS is used to exploit the local solution space to further improve the quality of a solution. The neighborhood of the TS is based on a disjunctive graph model, and a smaller neighborhood structure is adopted to reduce the computational cost of the neighborhood search. To reduce the solution space of JSPs and balance convergence speed and solution quality, scheduling solutions are restricted in the set of parameterized active schedules, i.e., a subset of active schedules. Forty-three benchmark instances are used to evaluate the proposed hybrid algorithm, and experimental results are compared with those of other algorithms. Results show that the hybrid algorithm is very effective for JSPs.     

An improved stopping condition guarantee recovery of sparse signal via Subspace Pursuit method

The Subspace Pursuit (SP) algorithm is one of greedy pursuit methods which is used to reconstruct of K-sparse signal. Unlike existing condition produced by Dai and Milenkovic in 2004 that suggests the residual value of current iteration is reduced from the previous iteration, our approach eliminates useless information by reducing the number of iterations used to detect the correct support set. This operation is done by suggesting a new halting condition that can capture the best support set which can give the best representation of the reconstructed signal. The new halting conditions enhanced the SP algorithm to low computational complexity and reconstruction accuracy of the sparse signal.A mathematically proven for two halt condition: noiseless setting, and noisy setting for signal affected by Gaussian noise. An error bound relation also is driven.In this paper, we try also to relax the restricted isometry constant RIC value to narrows the gap between the known bounds and ultimate performance, which it produced by Dai.Simulation results show that the new halting condition can overpass best results produce by earlier iteration and rise time consume. Our new halting condition can catch this earlier iteration and enhanced SP algorithm results.     

几何约束等价性及等价迭代研究

针对几何约束系统中不可构造的柔性复合顶点的求解问题,引入等价约束,分裂部分约束以打破柔性复合顶点的强耦合性,形成只包含简单顶点的求解序列。基于等价约束的性质和结构拓扑,研究了求解序列顶点存在与不存在实数解情况下,雅可比矩阵的求解方法,从而以少量分裂约束方程组对等价约束变量的等价迭代,或者柔性复合顶点的局部迭代,取代柔性复合顶点的整体数值迭代求解,降低迭代的维数,算法实现于几何约束求解引擎CBA(constraint broadcast automa-tion)中。     

The Gauss optimization method for problems with general nonlinear constraints

A new algorithm is presented for finding the minimum of a nonnegative objective function subject to general nonlinear constraints. This algorithm, based of Gauss’ method for unconstrained problems, is developed as an extension to the Gauss constrained technique for linear constraints. The derivation of the algorithm, using a Lagrange multiplier approach, is based on the Kuhn-Tucker conditions so that, when the iteration process terminates, these conditions are automatically satisfied. A feasible design is maintained throughout the iteration process. The solution of preliminary examples indicate excellent results in terms of the number of objective function evaluations required by the algorithm to obtain an optimal design.     

Penalty boundary sequential convex programming algorithm for non-convex optimal control problems

A nonlinear optimal control problem with non-convex cost function and non-convex state constraints can be addressed by a series of convex programming to obtain numerical solutions in previous methods. However, a feasible initial solution is essential to ensure the convergence. In this paper, slack variables are added into the model to handle the infeasible initial point and are penalized in the cost. What is more, a new approximation point on the boundary of constraints is embraced in each iteration to increase the similarity to original problem and decrease number of iterations. Thus, a penalty boundary sequential convex programming algorithm is proposed, which is globally convergent to a Karush-Kuhn-Tucker (KKT) point of original problem under mild condition. The theoretical basis is guaranteed by a rigorous proof. Single UAV and multi-robots trajectory planning serve as simulations to verify the validity of the presented algorithm.     

某雷达天线的结构设计与振动条件分解

雷达天线结构设计中,天线中的模块均根据整机振动条件进行设计,造成模块振动条件与真实工作状态的振动条件差别较大,甚至出现单独试验时正常的模块在随天线一起试验时发生损毁的现象.文中论述了某机载雷达天线的结构设计方案,在结构设计中将天线振动条件进行分解,得到天线中各模块的振动响应条件,为各模块的结构设计提供设计依据.同时将天线结构与功能一体化设计,实现天线轻型化设计的同时增加了天线负载的刚度贡献.最后,通过力学仿真和热仿真验证了该设计方案的可行性并通过了试验验证.     

道路模拟控制系统的研制和开发

介绍了道路模拟控制系统研制所采用的一套完整的实现方案，包括硬件系统的研制和软件核心算法的实现。在硬件系统研制部分，实现了多通道数据并行采集输出并使输出采集同步和大容量不间断数据采集输出的功能；在软件核心算法部分，介绍了所使用的频响估计算法、驱动信号迭代算法、驱动信号的连接和误差设定等问题。最后，给出了一个应用采用此方案所研制的道路模拟控制系统成功进行道路模拟试验的实例来验证了方案的正确性。     

Structural identification based on optimally weighted modal residuals

The structural parameter estimation problem based on measured modal data is often formulated as a weighted least-squares problem in which modal residuals measuring the fit between experimental and model predicted modal properties are build up into a single weighted residuals metric using weighting factors. Standard optimisation techniques are then used to find the optimal values of the structural parameters that minimise the weighted residuals metric. Due to model error and measurement noise, the results of the optimisation are affected by the values assumed for the weighting factors. In this work, the parameter estimation problem is first formulated as a multi-objective identification problem for which all Pareto optimal structural parameter values are obtained, corresponding to all possible values of the weights. A Bayesian statistical framework is then used to rationally select the optimal values of the weights based on the measured modal data. It is shown that the optimal weight value for a group of modal properties is asymptotically, for large number of measured data, inversely proportional to the optimal value of the residuals of the modal group. A computationally efficient algorithm is proposed for simultaneously obtaining the optimal weight values and the corresponding optimal values of the structural parameters. The proposed framework is illustrated using simulated data from a multi-dof spring–mass chain structure. In particular, compared to conventional parameter estimation techniques that are based on pre-selected values of the weights, it is demonstrated that the optimal parameter values estimated by the proposed methodology are insensitive to large model errors or bad measured modal data.     

基于滤波反投影的脑磁感应迭代重建算法研究

颅脑磁感应断层成像技术(BMIT)是一种非接触、无创的新兴颅脑医学成像技术,图像重建算法是提高重建图像质量的关键。依据BMIT反投影算法和迭代算法,设计出一套基于滤波反投影的脑磁感应迭代重建方法。首先根据滤波反投影重建算法原理,给出初始电导率分布,其次基于电导率变化敏感性加权计算滤波反投影矩阵,最后利用一步牛顿迭代构成滤波反投影迭代重建算法,通过设置理想条件数G来修正Hessian矩阵,改善重建过程的病态程度,并对待重建数据进行标准化位置校正处理。实验结果表明,该算法成像速度快,重建出的图像具有较高分辨率,能够准确反映成像区域内仿真病变的大小及位置信息,且轮廓清晰,为颅脑磁感应断层成像技术应用于临床监护奠定了基础。