汽轮机转子热应力在线计算灰色数学模型

热应力计算中边界条件、物性参数和初始条件等模型输入参数的灰色特性，使得以近似点值为输入得到的计算结果缺乏准确性依据和度量，该文提出的灰色数学模型，用区间数代替近似点值建立灰色数学模型，得出热应力在线计算值的灰色描述，可以更好地符合工程计算需要。文中针对模型应用的复杂程度，以汽轮机转子为对象，对单纯灰边界问题给出了简单的端点计算法及其依据；对复合灰边界灰物性问题建立了差分格式的数学模型，应用区间高斯迭代算法，结合模型结构特点推导了简易的基于内包含不等式的算法，并且给出两种算法的数值算例对比。     

Positive state‐bounding observer for positive interval continuous‐time systems with time delay

This paper is concerned with the problem of positive observer synthesis for positive systems with both interval parameter uncertainties and time delay. Conventional observers may no longer be applicable for such kind of systems due to the positivity constraint on the observers, and they only provide an estimate of the system state in an asymptotic way. A pair of positive observers with state‐bounding feature is proposed to estimate the state of positive systems at all times in this paper. A necessary and sufficient condition for the existence of desired observers is first established, and the observer matrices can be obtained easily through the solutions of a set of linear matrix inequalities (LMIs). Then, to reduce the error signal between the system state and its estimates, an iterative LMI algorithm is developed to compute the optimized state‐bounding observer matrices. Finally, a numerical example is presented to show the effectiveness and applicability of the theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

Analysis of nonlinear electrical circuits using bernstein polynomials

In electrical circuit analysis, it is often necessary to find the set of all direct current (d.c.) operating points (either voltages or currents) of nonlinear circuits. In general, these nonlinear equations are often represented as polynomial systems. In this paper, we address the problem of finding the solutions of nonlinear electrical circuits, which are modeled as systems of n polynomial equations contained in an n-dimensional box. Branch and Bound algorithms based on interval methods can give guaranteed enclosures for the solution. However, because of repeated evaluations of the function values, these methods tend to become slower. Branch and Bound algorithm based on Bernstein coefficients can be used to solve the systems of polynomial equations. This avoids the repeated evaluation of function values, but maintains more or less the same number of iterations as that of interval branch and bound methods. We propose an algorithm for obtaining the solution of polynomial systems, which includes a pruning step using Bernstein Krawczyk operator and a Bernstein Coefficient Contraction algorithm to obtain Bernstein coefficients of the new domain. We solved three circuit analysis problems using our proposed algorithm. We compared the performance of our proposed algorithm with INTLAB based solver and found that our proposed algorithm is more efficient and fast.     

一种基于风险传播的信息系统风险评估方法

传统信息系统的风险评估方法未考虑节点的状态变化和风险的传播方向,且评估结果的准确性受专家主观性的影响,对此,提出了一种基于风险传播的信息系统风险评估方法.首先,确定节点的初始状态转移概率矩阵,并根据攻击属性对矩阵进行修正,得到节点状态转移概率;其次,基于系统风险传播网络拓扑图和节点属性值计算节点在各方向的传播概率;然后,利用三参数区间数方法获取节点威胁事件的量化值;最后,根据风险评估方法计算各节点的风险值.实验结果表明,基于风险传播方法的评估流程更客观、合理,可提高信息系统风险评估的整体性和准确性.     

虚拟企业伙伴选择中模糊因素的定量评估

针对虚拟企业伙伴选择时存在不一致区间判断的复杂评估问题,组建战略联盟决策群并确定着眼于候选伙伴实现机遇的互补竞争力评价指标体系,提出在层次分析法(AHP)框架下,运用有下限和上限的区间数表达候选伙伴之间不一致、不确定的比较比例,获得区间比较矩阵,引入模糊集的隶属度函数表示对选择方案的满意程度,构造模糊约束集合,利用线性规划方法求解具有最大满意程度的优先权矢量,计算出候选者的总体优先顺序.结果表明,该方法能够从可行域为空的不一致区间比较矩阵导出模糊优先权矢量.列举的虚拟企业伙伴选择实例验证了应用这个方法从模糊判断矩阵计算出确定的优先权重的有效性,这是其他方法难以做到的.     

ESTIMATION OF THE PREDICTION ERROR VARIANCE AND AN R2 MEASURE BY AUTOREGRESSIVE MODEL FITTING

Abstract. For predicting the future values of a stationary process { x_t } ( t = 0, pL 1, pL 2,…) on the basis of its past, two key parameters are the variance V ( h ), h ≥ 1, of the h -step prediction error and Z ( h ) ={ R (0) - V ( h )}/ R (0), the corresponding measure, in an R ² sense, of the predictability of the process from its past, where R (0) denotes the process variance. The estimation of V ( h ) and Z ( h ) from a realization of T consecutive observations of { x_t } is considered, without requiring that the process follows a finite parameter model. Three different autoregressive estimators are examined and are shown to be asymptotically equivalent in the sense that as T ∝ they have the same asymptotic normal distribution. The question of bias in estimating these parameters is also examined and a bias correction is proposed. Finite sample behaviour is investigated by a simulation study.     

无约束非线性lp问题的区间极大熵方法

针对信号处理、系统识别等领域中涉及到的无约束非线性lp问题,为减小由于二进制编码的舍入误差对该问题计算结果的影响,对求解该问题的极大熵方法进行了区间扩张.证明了区间扩张后的极大熵函数至少具有二阶收敛性,并设计了具有多项式时间复杂度的区间算法进行求解,举例进行了数值计算.数值计算结果显示,该区间算法可靠,计算结果与区间扩张前相比,结果更加精确.     

Reliability analysis of a repairable duplex system

We analyse the survival time of a repairable duplex system characterised by cold standby and by a pre-emptive priority rule. We allow general probability distributions for failure and repair. Moreover, an important realistic feature of the system is the general assumption that the non-priority unit has a memory. This combination of features has not been analysed in the previous literature. Our (new) methodology is based on a concatenation of a Cauchy-type integral representation of the modified Heaviside unit-step function and a two-sided stochastic inequality. Finally, we introduce a security interval related to a security level and a suitable risk-criterion based on the survival function of the system. As a practical application, we analyse some particular cases of the survival function jointly with the security interval corresponding to a security level of 90.     

Stability Analysis and Controller Design of Discrete Interval Type‐2 Fuzzy Systems

This paper is concerned with trajectory stabilization of a computer simulated model car with uncertain velocity via type‐2 fuzzy control systems. First, stability conditions of discrete interval type‐2 fuzzy control systems are given in accordance with the definition of stability in the sense of Lyapunov. Then, we approximate a computer simulated model car, whose dynamics are nonlinear and velocity is uncertain. A type‐2 Takagi–Sugeno TS fuzzy controller is designed to handle system uncertainty. The control rules, which guarantee stability of the system, are derived from the approximated model. The simulation results show that the type‐2 fuzzy control rules can effectively stabilize the car model.     

一类区间多目标粒子群优化算法

针对区间参数多目标优化问题,提出一种基于模糊支配的多目标粒子群优化算法。首先,定义基于决策者悲观程度的模糊支配关系,用于比较解的优劣;然后,定义一种适于区间目标值的拥挤距离,以更新外部存储器并从中选择领导粒子;最后,对多个区间多目标测试函数进行仿真实验,实验结果验证了所提出算法的有效性。