Exponential stabilization of uncertain time‐delay linear systems with Markovian jumping parameters

This paper studies the exponential stabilization problem of uncertain time‐delay linear systems with Markovian jumping parameters. A novel delay decomposition approach is developed to derive delay‐dependent conditions under which the closed‐loop control system is mean square exponentially stable for all admissible uncertainties. It is shown that the feedback gain matrices and the decay rate can be obtained by solving coupled linear matrix inequalities. Moreover, the difficulties arising from searching for tuning parameters in the existing methods are overcome. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Feedback predictive control for constrained fuzzy systems with Markovian jumps

In this paper, a feedback model predictive control method is presented to tackle control problems with constrained multivariables for uncertain discrete‐time nonlinear Markovian jump systems. An uncertain Markovian jump fuzzy system (MJFS) is obtained by employing the Takagi‐Sugeno (T‐S) fuzzy model to represent a discrete‐time nonlinear system with norm bounded uncertainties and Markovain jump parameters. To achieve more generality, the transition probabilities of the Markov chain are assumed to be partly unknown and partly accessible. The predictive formulation adopts an on‐line optimization paradigm that utilizes the closed‐loop state feedback controller and is solved using the standard semi‐definite programming (SDP). To reduce the on‐line computational burden, a mode independent control move is calculated at every sampling time based on a stochastic fuzzy Lyapunov function (FLF) and a parallel distributed compensation (PDC) scheme. The robust mean square stability, performance minimization and constraint satisfaction properties are guaranteed under the control move for all admissible uncertainties. A numerical example is given to show the efficiency of the developed approach. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

基于综合优化方法的风力发电机故障诊断

支持向量机(SVM)一种新型的统计学习方法。但是作为分类算法,它存在计算量大、运行时间长的缺点。针对LSSVM的参数选择问题,引入物理学中的黑洞概念,建立黑洞模型,结合模拟退火算法,提出了黑洞粒子群-模拟退火算法(BH-PSOSA)。该算法可以增加粒子的多样性,克服PSO算法优化过程中陷入局部极值的问题,提高了优化性能,改善了收敛特性。利用BHPSO-SA算法对LSSVM的参数进行优化选择,用UCI数据库的数据进行分类验证,相比CV参数优化的LSSVM,提高了分类速度和精度。最后把BHPSOSA-LSSVM算法应用到风机齿轮箱的故障诊断中,取得了良好的效果。     

Study of viscosity of mono-, di-, and trialkylamines

Viscosities of several mono-, di-, and trialkylamines have been measured in the temperature range 298 to 333 K. It is observed that viscosities are highly dependent on shape, size, and association through H-bond or through dipole. Following the transition state theory, energy, Gibbs free energy, and entropy of activation of viscous flow have been calculated. The values of expansion energy for these liquids have also been calculated using free volume theory, and subsequently amines have been classified as volume-restrained or energy-restrained liquids. The group contribution method of Van Velzen, Cardozo, and Langenkamp for estimating viscosity has been examined with the present and literature data, and the new group contribution increments N _i and B _i for amines have been evaluated.     

An experimental study of the thermodynamic properties of 1,1-difluoroethane

Experimental vapor pressures andP--T data of an important alternative refrigerant, 1, 1-difluoroethane (HFC-152a), have been measured by means of a constant-volume method coupled with expansion procedures. SixtyP--T data were measured along eight isochores in a range of temperaturesT from 330 to 440 K, at pressuresP from 1.6 to 9.3 MPa, and at densities from 51 to 811 kg·m^–3. Forty-six vapor pressures were also measured at temperatures from 320 K to the critical temperature. The uncertainties of the temperature and pressure measurements are within ±7mK and ±2kPa, respectively, while the uncertainty of the density values is within ±0.1%. The purity of the sample used is 99.9 wt%. On the basis of the measurements along each isochore, five saturation points were determined and the critical pressure was determined by correlating the vapor-pressure measurements. The second and third virial coefficients for temperatures from 360 to 440 K have also been determined.     

遥感图像理想均衡化及图像质量定量评价

大多数原始的遥感影像由于其灰度分布集中在较窄的范围内,影像的细节不够清晰,对比度较低。为了使影像的灰度范围拉开或使灰度均匀分布,从而增大反差,增强影像细节信息,通常采用的方法为直方图均衡化。通过对信息熵定义的阐述,引出直方图均衡化的图像增强算法。通过分析传统直方图均衡化算法中存在的缺陷,进而基于分段映射思想提出一种改进的理想直方图均衡化算法。同时,为了对传统算法和改进算法进行定量化地分析比较,基于同时对比度以及人类视觉对比度分辨率限制和模糊数学的相关思想,分别提出基于加权几何平均数法的合成平均对比度和细节评价参数的定义。最后,采用同时对比度、基于加权几何平均数法的合成平均对比度以及细节评价参数作为定量评价的指标,对所提出的改进算法进行了定量评价。评价结果表明,该改进算法的图像增强效果优于传统的直方图均衡化算法。     

鸟体动力学本构模型参数反演的并行优化技术

研究鸟体本构模型的动力学过程,是飞行器抗鸟撞,保证飞行安全的重要问题。由于鸟体模型参数难确定,为得到准确而合理的鸟体参数,在已知鸟体本构模型的前提下,采用并行优化技术对本构参数进行反演。将鸟撞平板的试验结果与数值仿真结果的相对误差平方和最小作为目标函数,将待反演的鸟体参数作为设计变量,在同一撞击速度范围内,将鸟撞不同靶板分为不同工况构造并行优化反演模型。把反演得到的鸟体参数代回到鸟撞平板仿真模型中检验,经与试验结果对比,效果较好,表明采用的并行优化技术是有效的、可靠的。并行优化反演技术的实现为更准确的获取鸟体参数提供了新的思路和方法,也为提高飞行器抗鸟撞设计研究提供有益参考。     

一种基于UML状态图的规约变异测试方法

规约变异测试从软件功能的角度,对规约进行分析,从而揭示规约中存在的问题。本文提出一种基于UML状态图的变异测试方法,针对每种变异算子,分析其是否会引入冲突,进而有效避免不合理的变异操作;分析了每种变异算子产生等价变异体的条件,能够在生成变异体的同时检测并移除等价变异体,进而减少其对测试过程的影响;给出了杀掉每种变异体所需满足的条件,可在此基础上产生杀掉特定变异体所需的测试用例,从而提高测试用例集的质量。在此基础上,根据变异算子的实际功能,整合了功能相同的算子,减少了变异算子的数量,从而进一步降低了变异测试的开销。实验结果表明,本方法能够较好地提高测试用例的质量,进而提升测试的效率。     

Planning for the Subernarekha river system in eastern India

The study describes the systems studies carried out to plan a river basin in order to determine the nature and size of water storage facilities and releases for irrigation and industrial uses, and the associated cropping pattern. The model has been formulated in the framework of a linear programming model for a specific target year. This model is developed in the context of planning the Subernarekha river basin. The results are discussed and these provide information and insight suggesting the need for more disaggregated analysis of interaction between irrigation and related agroeconomic parameters.     

The statistical modeling of surface roughness in high-speed flat end milling

Surface roughness is one of the most important requirements in machining process. The surface roughness value is a result of the tool wear. When tool wear increase, the surface roughness also increases. The determination of the sufficient cutting parameters is a very important process obtained by means of both minimum surface roughness values and long tool life. The statistical models were developed to predict the surface roughness.This paper presents the development of a statistical model for surface roughness estimation in a high-speed flat end milling process under wet cutting conditions, using machining variables such as spindle speed, feed rate, depth of cut, and step over. First- and second-order models were developed using experimental results of a rotatable central composite design, and assessed by means of various statistical tests. The highest coefficient of correlation (R_adj²) (88%) was obtained with a 10-parameter second-order model. Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting the probable effect of the tool wear on surface roughness. Thus, in order to enhance the estimation capability of the model, another independent variable was included into the model to account for the effect of the tool wear, and the total operating time of the tool was selected as the most suitable variable for this purpose. By inserting this new variable as a linear term into the model, R_adj² was increased to 94% and a good fit was observed between the model predictions and supplementary experimental data.In this study, it was observed that, the order of significance of the main variables is as X₅>X₃>X₄>X₁>X₂ (total machining time, depth of cut, step over, spindle speed and feed rate, respectively).