基于LuGre模型非光滑柱铰链平面多体系统动力学的建模和数值方法

以含非光滑柱铰链平面多刚体系统为研究对象,将间隙充分小的柱铰链视为双边约束,用LuGre摩擦模型描述柱铰链内的摩擦;由第一类Lagrange方程导出该系统的动力学方程(微分 代数方程).铰链处的摩擦使得其动力学方程是关于Lagrange乘子的非线性代数方程组,由于LuGre摩擦模型具有很好的连续性,可将非线性代数方程组与常微分方程组的数值算法(如拟牛顿法和龙格 库塔法)相结合求解其动力学方程.最后,通过数值仿真算例说明了该算法的可行性和有效性,既能很好地反映柱铰链摩擦对系统动力学特性的影响,又能避免Coulomb干摩擦给方程求解带来的困难.     

Modelling time-varying higher moments with maximum entropy density

Since the introduction of the Autoregressive Conditional Heteroscedasticity (ARCH) model of Engle [R. Engle, Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica 50 (1982) 987–1007], the literature of modelling the conditional second moment has become increasingly popular in the last two decades. Many extensions and alternate models of the original ARCH have been proposed in the literature aiming to capture the dynamics of volatility more accurately. Interestingly, the Quasi Maximum Likelihood Estimator (QMLE) with normal density is typically used to estimate the parameters in these models. As such, the higher moments of the underlying distribution are assumed to be the same as those of the normal distribution. However, various studies reveal that the higher moments, such as skewness and kurtosis of the distribution of financial returns are not likely to be the same as the normal distribution, and in some cases, they are not even constant over time. These have significant implications in risk management, especially in the calculation of Value-at-Risk (VaR) which focuses on the negative quantile of the return distribution. Failed to accurately capture the shape of the negative quantile would produce inaccurate measure of risk, and subsequently lead to misleading decision in risk management. This paper proposes a solution to model the distribution of financial returns more accurately by introducing a general framework to model the distribution of financial returns using maximum entropy density (MED). The main advantage of MED is that it provides a general framework to estimate the distribution function directly based on a given set of data, and it provides a convenient framework to model higher order moments up to any arbitrary finite order k. However this flexibility comes with a high cost in computational time as k increases, therefore this paper proposes an alternative model that would reduce computation time substantially. Moreover, the sensitivity of the parameters in the MED with respect to the dynamic changes of moments is derived analytically. This result is important as it relates the dynamic structure of the moments to the parameters in the MED. The usefulness of this approach will be demonstrated using 5 min intra-daily returns of the Euro/USD exchange rate.     

运动滑道含摩擦多体系统的建模和数值方法

研究了运动约束面含摩擦多体系统动力学方程的建立和算法问题．首先利用第一类Lagrange方程给出了系统的动力学方程,并以矩阵形式给出了这类系统摩擦力的广义力的一般表达式．为便于摩擦力和铰链约束力的分析与计算,采用笛卡尔坐标和约束方程的局部方法,使得系统的约束力与Lagrange乘子一一对应．应用增广法将微分一代数方程组转化为常微分方程组并用分块矩阵的形式给出,以便于方程的编程与计算,提高计算效率．最后用一个算例验证了该方法的有效性．     

两级磁悬浮工作平台的动力学建模及模态分析

一级磁悬浮工作平台往往只能实现一维直线运动，因此建立能够实现平面运动的两级磁悬浮工作平台便成为研究需要。以一个两级磁悬浮工作平台为对象，从力学、物理与控制等基本原理出发，利用拉格朗日方程，建立了能够全面反映其耦合特性的动力学方程。进行模态分析后发现两级磁悬浮平台的固有频率和振型随上悬浮平台悬浮位置的不同而变化很小。平台动力学方程的建立和模态分析能够为控制器的设计和控制参数的选取及优化提供参考。     

Identification environment and robust forecasting for nonlinear time series

In this paper, the methods of time series for nonlinearity are briefly surveyed, with particular attention paid to a new test design based on a neural network specification. The proposed integrated expert system contains two main components: an identification environment and a robust forecasting design. The identification environment can be viewed as a integrated dynamic design in which cognitive capabilities arise as a direct consequence of their self-organizational properties. The integrated framework used for discussing the similarities and differences in the nonlinear time series behavior is presented. Moreover, its performance in prediction proves to be superior than the former work. For the investigation of robust forecasting, we perform a simulation study to demonstrate the applicability and the forecasting performance.     

Cryptanalysis and improvement of nonrepudiable threshold multi-proxy multi-signature scheme with shared verification

Recently, Tzeng et al. proposed a nonrepudiable threshold multi-proxy multi-signature scheme with shared verification. In their scheme, a subset of original signers can delegate the signing power to a group of the designated proxy signers in such a way that: (i) A valid proxy signature can only be generated by a subset of these proxy signers for a group of the designated verifiers. (ii) The validity of the generated proxy signature can only be verified by a subset of the designated verifiers. This article, however, will demonstrate a security leak inherent in Tzeng et al.’s scheme that any verifier can check the validity of the proxy signature by himself with no help of other verifiers. That is, Tzeng et al.’s scheme cannot achieve their claimed security requirement. Finally, we will propose an improvement to eliminate the pointed out security leak.     

Web应用程序建模和测试用例生成方法

根据基于组件的Web应用程序的特点,提出逻辑组件的概念。按功能将待测系统划分成逻辑组件,并在功能上将其对应到实际组件。利用有向图表示逻辑组件结构关系,自动机表示逻辑组件的行为关系,自动机的复合表示逻辑组件间的交互操作。根据复合的自动机,利用建立的操作映射表生成测试用例。分析了一个测试准则,并提出逻辑组件测试序列的覆盖度概念。     

自动驾驶交叉路口测试场景建模及验证方法

自动驾驶汽车在缓解交通拥堵和消除交通事故方面发挥着重要作用.为了保证自动驾驶系统的安全性和可靠性,在自动驾驶汽车部署到公共道路之前,必须进行全面的测试.现有的测试场景数据大多来源于交通事故和交通违法场景,而且自动驾驶系统最基本的安全需求就是遵守交通法规,这充分体现了自动驾驶汽车遵守交通规则的重要性.然而,目前严重缺少针对交通法规构建的自动驾驶测试场景.因此,本文从交通法规出发,根据自动驾驶系统安全需求,提出交叉路口测试场景的Petri网建模及形式化验证方法.首先,依据自动驾驶测试场景对交规进行分类,提取适合自动驾驶汽车的文本交规,并进行半形式化表征.其次,以覆盖道路交通安全法规以及测试场景功能测试规程为目标,融合交叉路口场景要素的交互行为,合理选择并组合测试场景要素,布设交叉路口测试场景.然后,基于交规的测试场景被建模为一个Petri网,其中,库所描述自动驾驶汽车的状态,变迁表示状态的触发条件,并选择时钟约束规范语言（CCSL）作为中间语义语言,将Petri网转换为一个可进行形式化验证的中间语义模型,提出具体的转换方法.最后,通过Tina软件分析验证交规场景模型的活性、有界性和可达性,结果表明所建模型的正确性,并基于SMT的分析工具MyCCSL来分析CCSL约束,采用LTL公式以形式化方法验证交规场景模型的一致性.     

气候环境实验室建模及温度控制系统仿真

气候环境实验室是一个复杂的热力系统,室内温度参数受多种因素的影响.通过分析气候环境实验室仓体、空调系统热交换器、温度传感器和调节阀的特性,推导出它们的传递函数,利用Matlab/Simu-link建立环境室温度控制系统的模型,根据临界比例度法整定PID参数,并对常规PID控制器和积分分离PID控制器的控制效果进行仿真比较.仿真结果表明该模型和温度控制系统在理论研究和工程实践中具有实际的指导意义和应用价值.     

分布式软件系统交互行为建模、验证与测试

为了确保分析与设计阶段分布式软件系统中模块之间交互行为的正确性,提出了一种分布式软件系统模块交互的抽象方法,分别通过系统状态机图和对象状态机图对各模块状态变迁进行建模,使用UML2.0序列图对模块之间交互行为进行描述.采用基于命题投影时序逻辑的模型检测技术,将对象状态机图转换为Promela模型,系统交互性质转换为命题投影时序逻辑公式,通过模型检测器验证交互模型是否满足于系统的性质,若不满足于该性质,则能够获得反例执行的路径.给出了一个分布式软件系统测试框架,在验证后的序列图模型基础上,使用基于模型的测试用例自动生成方法得到测试用例集合,该集合能够实现对交互行为的有效测试.实例结果表明,该方法可以提高分布式软件系统中模块交互行为的有效性和可靠性.     

基于ORD和FSM的Web应用的建模与测试

Web测试是保证高质量Web应用的一种有效技术.然而,由于其特殊性和复杂性,很难直接将传统的测试理论与方法学运用到Web应用的测试当中来.对Web应用进行了分析与建模,并对其进行测试,提出了一种可行的Web测试模型.首先得到页面流图(PFD,Page Flow Diagram),进而产生对象关系图(ORD,Object Relation Diagram),然后根据提出的算法将ORD转化为形式化的有限状态机(FSM,Finite State Machine)模型.基于FSM模型,提出了一种有效的测试路径自动生成方法,这些测试路径可以转化为XML语法的测试规格说明.测试引擎将测试规格说明作为输入最终产生测试报告.全文以所开发的一个小型的Web应用SWLS(Simple Web Login System)为例进行阐述.     

基于局部模型网络的超声波浓度测量和在线校正

在很多情况下 ,液体浓度是其声速的函数 ,而且在不同的温度点上 ,这种函数关系是不同的 .针对浓度、声速和温度关系的这种特点 ,本文提出了基于局部模型网络的浓度和声速、温度关系的拟合和校正方法 .这种方法比普通的多项式拟合具有更多的灵活性和适用性 ,易于在线进行 .     

基于Karnopp摩擦的柔性滑移铰的建模与仿真

对含Karnopp摩擦的柔性滑移铰系统进行动力学建模和仿真.将滑移铰中的滑块视为柔性体,滑道视为刚性接触面,考虑滑道与滑块之间的间隙.由于柔性滑块与滑道的接触状态和摩擦情况比较复杂,采用有限元方法建立了柔性滑块的力学模型,基于罚函数方法建立含Karnopp摩擦柔性滑移铰接触力模型,通过试算迭代法判断柔性滑块各节点的接触状态,基于KED方法和Newmark方法给出了含该滑移铰机械系统动力学方程的数值算法.最后,以含Karnopp摩擦的柔性滑移铰和驱动摆杆构成的机械系统为例进行动力学仿真,分析了其动力学特性,验证了本文给出的方法的有效性.     

飞行管理系统AADL建模与分析

航空电子系统软件的建模与分析是保证军用和民用飞机高可靠、高性能的重要手段,也是模型驱动软件体系结构的重要组成部分。飞行管理系统作为航空电子系统的重要组成部分,传统上,对该系统的可调度性分析是在系统设计完成后,在实现与验证阶段进行的,这使得系统无法进行的准确地软硬件需求分析。采用先进的建模方法AADL对其进行建模,为飞行管理系统的可调度性分析、可靠性分析以及通信延迟等分析提供了可能,使得在系统需求分析阶段就可以准确确定系统的软硬件需求,并能大大降低系统的更改验证成本。首先论述了建模语言AADL的基本构成以及与航空电子应用接口规范ARING653的对应关系;然后描述了飞行管理系统的功能构成,并建立了飞行管理系统的AADL模型;最后详细论述了系统调度理论,AADL工具,飞管系统AADL模型的仿真分析。通过仿真分析为飞管系统的处理器选型、系统设计、软件设计与优化提供了依据。     

Application of VPRS model with enhanced threshold parameter selection mechanism to automatic stock market forecasting and portfolio selection

This study proposes a technique based upon Fuzzy C-Means (FCM) classification theory and related fuzzy theories for choosing an appropriate value of the Variable Precision Rough Set (VPRS) threshold parameter (β) when applied to the classification of continuous information systems. The VPRS model is then combined with a moving Average Autoregressive Exogenous (ARX) prediction model and Grey Systems theory to create an automatic stock market forecasting and portfolio selection mechanism. In the proposed mechanism, financial data are collected automatically every quarter and are input to an ARX prediction model to forecast the future trends of the collected data over the next quarter or half-year period. The forecast data are then reduced using a GM(1, N) model, classified using a FCM clustering algorithm, and then supplied to a VPRS classification module which selects appropriate investment stocks in accordance with a pre-determined set of decision-making rules. Finally, a grey relational analysis technique is employed to weight the selected stocks in such a way as to maximize the rate of return of the stock portfolio. The validity of the proposed approach is demonstrated using electronic stock data extracted from the financial database maintained by the Taiwan Economic Journal (TEJ). The portfolio results obtained using the proposed hybrid model are compared with those obtained using a Rough Set (RS) selection model. The effects of the number of attributes of the RS lower approximation set and VPRS β-lower approximation set on the classification are systematically examined and compared. Overall, the results show that the proposed stock forecasting and stock selection mechanism not only yields a greater number of selected stocks in the β-lower approximation set than in the RS approximation set, but also yields a greater rate of return.     

PSO并行优化LSSVR非线性黑箱模型辨识

针对非线性黑箱系统辨识中存在不确定性、高阶次,采用常规辨识方法建立其精确数学模型十分困难等问题,提出一种基于自适应粒子群算法的最小二乘支持向量机回归(PSO-LSSVR)非线性系统辨识方法.该方法采用2组自适应粒子群算法并行计算模型,分别利用自适应粒子群算法对LSSVR中的参数进行自动选取和矩阵迭代求解,既克服了传统LSSVR参数难以确定的缺点,提高了辨识精度,同时避免了复杂矩阵求逆运算,加快了计算速度.将该方法应用于船舶操纵性模型非线性系统辨识,仿真结果表明,由该方法得到的LSSVR能够有效地对系统进行建模,仿真精度高,结构简单,具有一定的理论推广意义.     

Modeling and robust adaptive iterative learning control of a vehicle‐based flexible manipulator with uncertainties

In this brief, this paper deals with a robust adaptive iterative learning control (ILC) problem for a flexible manipulator attached to a moving vehicle with uncertainties. To begin with, considering the infinite dimensionality of the flexible distributed parameter system, a coupled ordinary differential equation and partial differential equation model is established without any discretization. Then, it is followed by a presentation of an adaptive ILC strategy, which can drive the vehicle and joint to the desired positions based on a proportional‐derivative feedback structure with unmodeled dynamics and external disturbances. The deformation of the flexible manipulator can also be suppressed simultaneously under the proposed control laws. By using Lyapunov's direct method, the stability of the closed‐loop system is demonstrated. The simulation results are provided to illustrate the effectiveness of the proposed control laws.