Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

机载光电雷达它机试飞技术研究

机载光电雷达受平台及大气环境影响较大,而它机试飞能有效规避研制风险,是产品研制的必经阶段。本文介绍了机载光电雷达它机试飞试验系统组成、试验流程和数据处理等内容。经工程验证,实施过程满足任务需求,对其他光电系统的它机及本机试飞具有参考价值。     

带延迟索赔和随机收入的离散风险模型的Gerber-Shiu分析（英）

破产理论是保险数学中的重要问题，它可以为保险公司决策者提供一个非常有用的早期风险预警手段．本文研究了一个带潜在延迟索赔和随机保费收入的复合二项风险模型．利用矩母函数的技巧，得到了 Gerber-Shiu 期望折罚函数的递推公式．特别地，还得到了贴现因子为 1 的特殊情形下的 Gerber-Shiu 期望折罚函数的解析表达式．最后还得到了实际应用中的一些重要的破产特征量，包括破产概率，破产时赤字的密度函数，破产前盈余与破产时赤字的联合密度函数，以及导致破产的索赔密度函数等．     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

马氏体-奥氏体复合钢复合层数对组织性能的影响

 开发更高性能的钢铁材料是促进“双碳”目标达成的有效途径之一。引入碳扩散是制备超高强度-高塑性复合钢的有效方法。在课题组前期研究基础上,利用真空热轧的方式制备不同层数的复合钢。通过增加层数,减小了复合钢内各层的厚度,复合钢在1 150 ℃热轧复合后继续保温过程,实现碳元素从高碳层向低碳层的扩散。利用扫描电子显微镜、FEI-透射电子显微镜及X射线衍射仪对组织及相组成进行了分析,利用电子探针显微分析仪测量了元素分配情况,并进行了硬度和拉伸性能测试。结果表明,随着层数的增加,复合钢内碳元素分布发生了明显的变化,马氏体层内部的碳含量逐渐升高,奥氏体层内部的碳含量逐渐降低,碳元素浓度差逐渐降低。同时,复合钢的屈服强度、抗拉强度和总伸长率呈现出先增加后降低的趋势。当复合钢内层数为9、11层时,其强度和塑性均超过单层马氏体钢;均匀伸长率随复合钢层数的增加而逐渐提高,15层复合钢取得了最大值(约10.1%)。9层复合钢获得了最佳的强度和塑性组合,与单层马氏体钢相比,抗拉强度(1 733 MPa)和伸长率(23.6%)分别提高了60 MPa和7.1%;同时其塑性也超过了单层奥氏体钢。此外,随着层数的增加,也导致奥氏体层比例逐渐提高,导致15层复合钢的强度低于单层马氏体钢的强度。     

一种外LET柔顺半铰的动力学建模与分析

对一种外LET柔顺半铰进行建模与动力学特性分析。采用斜率不连续的绝对节点坐标法（ANCF）建立了该柔顺半铰系统动力学方程；对外力作用下半铰中心线和外轮廓的运动变形进行仿真，与实验结果对比，证明了绝对节点坐标法对柔顺半铰动力学建模的有效性；进一步分析了半铰外形尺寸变化对其变形规律的影响。     

控制点CGCS2000坐标的联测及解求

CGCS2000坐标系是我国目前精度最高的坐标系,其推广使用具有重大意义。文中在安装并学习美国高精度GPS基线处理软件GAMIT软件基础上,以4个无坐标信息观测墩为例,进行观测数据采集与数据处理方案的设计,以期获取4个观测墩的CGCS2000坐标。最终结果表明,各质量指标均满足限差要求,且平差后最弱边中误差满足《工程测量规范》(GB50026-2007)三等工程控制网的要求。     

Monitoring of degradation of porous silicon photonic crystals using digital photography

We report the monitoring of porous silicon (pSi) degradation in aqueous solutions using a consumer-grade digital camera. To facilitate optical monitoring, the pSi samples were prepared as one-dimensional photonic crystals (rugate filters) by electrochemical etching of highly doped p-type Si wafers using a periodic etch waveform. Two pSi formulations, representing chemistries relevant for self-reporting drug delivery applications, were tested: freshly etched pSi (fpSi) and fpSi coated with the biodegradable polymer chitosan (pSi-ch). Accelerated degradation of the samples in an ethanol-containing pH 10 aqueous basic buffer was monitored in situ by digital imaging with a consumer-grade digital camera with simultaneous optical reflectance spectrophotometric point measurements. As the nanostructured porous silicon matrix dissolved, a hypsochromic shift in the wavelength of the rugate reflectance peak resulted in visible color changes from red to green. While the H coordinate in the hue, saturation, and value (HSV) color space calculated using the as-acquired photographs was a good monitor of degradation at short times (t < 100 min), it was not a useful monitor of sample degradation at longer times since it was influenced by reflections of the broad spectral output of the lamp as well as from the narrow rugate reflectance band. A monotonic relationship was observed between the wavelength of the rugate reflectance peak and an H parameter value calculated from the average red-green-blue (RGB) values of each image by first independently normalizing each channel (R, G, and B) using their maximum and minimum value over the time course of the degradation process. Spectrophotometric measurements and digital image analysis using this H parameter gave consistent relative stabilities of the samples as fpSi > pSi-ch.     

Prediction of the crack condition of highway pavements using machine learning models

Departments of Transportation regularly evaluate the condition of pavements through visual inspections, nondestructive evaluations, image recognition models and learning algorithms. The above methodologies, though efficient, have drawn attention due to their subjective errors, uncertainties, noise effects and overfitting. To improve on the outcomes of the shallow learning models already used in pavement crack prediction, this paper reports on an investigation of the use of recursive partitioning and artificial neural networks (ANN; deep learning frameworks) in predicting the crack rating of pavements. Explanatory variables such as the average daily traffic and truck factor, roadway functional class, asphalt thickness, and pavement condition time series data are employed in the model formulation. Overall, it is observed that the recursive partitioning (regression tree – R² > 0.8 and classification tree – R² > 0.6) and ANN (continuous response – R² > 0.8 and categorical response – R² > 0.6) are compelling machine learning models for the prediction of the crack ratings based on their goodness-of-fit statistics, mean absolute deviation (MAD < 0.4) and the root mean square errors (RMSE between 0.30 and 0.65).     

基于马达-垫圈的几何形状坐标新算法研究

为提高SCARA机器人机械臂末端执行器的操纵精度,提出一种基于马达-垫圈的几何形状坐标新算法。通过对某款运用仿生设计理论的SCARA机械臂的马达-垫圈装配设备开展视觉处理及精度控制技术研究,对末端执行器采集的马达和垫圈图像进行了图像处理,并基于模板特征进行了垫圈圆心和马达圆心的识别与定位,根据马达模具的几何形状提出一种基于拍3次图像的马达坐标计算方法;进行末端执行器定位精度控制试验,并验证该算法的可行性。结果表明:试验结果远远小于马达装配精度所要求的0.2 mm,证明了该算法能够有效地提高末端执行器的定位精度。