An application of the Kriging method in global sensitivity analysis with parameter uncertainty

For structural systems with both epistemic and aleatory uncertainties, the effect of epistemic uncertainty on failure probability is measured by the variance based sensitivity analysis, which generally needs a “triple-loop” crude sampling procedure to solve and is time consuming. Thus, the Kriging method is employed to avoid the complex sampling procedure and improve the computational efficiency. By utilizing the Kriging predictor model, the conditional expectation of failure probability on the given epistemic uncertainty can be calculated efficiently. Compared with the Sobol’s method, the proposed one can ensure reasonable accuracy of results but with lower computational cost. Three examples are employed to demonstrate the reasonability and efficiency of the proposed method.     

Precise bounds for the petersen time-varying real parameter uncertainty system stabilized via linear static controllers

Using a class of linear static controllers, we stabilize the Petersen open-loop two-dimensional linear system (Ref. 1), which consists of one time-varying uncertainty in the state matrixA and one timevarying uncertainty in the input matrixB. We show that the worst-case uncertainty strategy for the closed-loop system is a piecewise constant strategy of the angular state with three switches on the half-turn, –/2/2; it is unique with respect to a set of measure zero. Formulas are derived for the worst-case half-turn radius gainr _HT as a function of the parameters of the class of stabilizing linear static controllers. Using the class of scalar-quadratic Lyapunov functions, we show that a necessary and sufficient condition for the closed-loop system to be robustly stable against all time-varying admissible uncertainties is thatr _HT be less than unity. The bound on the time-varying real parameter uncertainties for the closed-loop system to be robustly stable is derived for the class of linear static feedback controllers. We obtain stabilizing linear static controllers such that the bound is as close to infinity as desired. The derived results are compared with numerical results obtained using commerical robust-control software.     

State estimation for Markov-type genetic regulatory networks with delays and uncertain mode transition rates

This Letter is concerned with the robust state estimation problem for uncertain time-delay Markovian jumping genetic regulatory networks (GRNs) with SUM logic, where the uncertainties enter into both the network parameters and the mode transition rate. The nonlinear functions describing the feedback regulation are assumed to satisfy the sector-like conditions. The main purpose of the problem addressed is to design a linear estimator to approximate the true concentrations of the mRNA and protein through available measurement outputs. By resorting to the Lyapunov functional method and some stochastic analysis tools, it is shown that if a set of linear matrix inequalities (LMIs) is feasible, the desired state estimator, that can ensure the estimation error dynamics to be globally robustly asymptotically stable in the mean square, exists. The obtained LMI conditions are dependent on both the lower and the upper bounds of the delays. An illustrative example is presented to demonstrate the feasibility of the proposed estimation schemes.     

大幅提高视觉密度国家基准测量水平的方法研究

随着生物医学影像和航天军事测量的发展,对用于光学成像底片和视觉校正的视觉密度的测量范围和不确定度的要求越来越高.以自行设计的光纤半球发射器形成的复合漫射器为特征的新方案将视觉漫透射密度国家基准的光源漫射系数提高到0.945,比欧美国家基准高0.02—0.03.实验得到新基准的测量范围为0—6.0,合成不确定度为0.0015(0相似文献   

基本物理化学常数的CODATA最新推荐值

文章给出了由国际科学技术数据委员会（简称CODATA）推荐的基本物理化学常数及转换因子的1998的自洽组的数值,供国际上普遍使用。新推荐值的村准不确定度,与1986年推荐值的相应不确定度比较,在多数情况下,前约为后者的1／5至1／12,而在某些情况下,则为其1／160,然后,几科在所有情况下,1998年数值与1986年相应值之差的绝对值均小于1986年数值的标准不确定度的两倍。     

Optimal entropic uncertainty relation for successive measurements in quantum information theory

We derive an optimal bound on the sum of entropic uncertainties of two or more observables when they are sequentially measured on the same ensemble of systems. This optimal bound is shown to be greater than or equal to the bounds derived in the literature on the sum of entropie uncertainties of two observables which are measured on distinct but identically prepared ensembles of systems. In the case of a two-dimensional Hilbert space, the optimum bound for successive measurements of two-spin components, is seen to be strictly greater than the optimal bound for the case when they are measured on distinct ensembles, except when the spin components are mutually parallel or perpendicular     

不确定非线性动力系统的稳定性分析

本文讨论渐近稳定的非线性名义动力系统在非线性时变扰动下的鲁棒稳定性问题。应用Ｌｙａｐｕｎｏｖ稳定性定理及其推广定理得出了非线性动力系统鲁棒稳定的若干判别准则，并给邮了应用所得准则的实际算例。