输入采用广义梯形隶属函数的最简模糊控制器结构分析

总结了应用最为广泛的三角形和梯形隶属函数的共同特点，明确定义了一种将以上两种隶属函数作为特例的广义梯形（GTS）隶属函数，推导了输入空间采用一致GTS（CGTS）模糊分划的两维最简模糊控制器的解析表达式。在此基础上，深入研究了CGTS模糊控制器的解析结构，证明了该模糊控制器等价于一种变结构的线性PI控制器与相应的定常控制偏置之和，并且在其输入论域上是单调递增、连续且有界的，同时揭示了此类控制器是一种更一般化的模糊控制器。     

典型模糊控制器的插值形式

推导出了单输入单输出、双输入单输出典型Mamdani模糊控制器的插值解析表达式，并推广到输出采用输入变量函数的典型T—S模糊控制器。典型Mamdani模糊控制器的输入采用正规模糊集、三角形全交迭的隶属函数，输出采用单点模糊数。这些插值表达式在一定程度上揭示了典型模糊控制器的本质特征，为设计和优化提供了准确的解析模型，同时也为模糊控制器的实际应用提供了一种快速精确的控制算法。     

带积分环节的隶属度函数中心自适应模糊控制器设计

自适应变论域模糊控制是改变模糊控制性能的主要方法之一,针对自适应变论域模糊控制器的稳定性设计这一难题,将输入和输出的隶属度函数分别用论域值表示成解析形式;针对典型模糊控制系统没有考虑积分环节带来的稳态误差问题,设计一种积分器,并从减小控制规则数目的角度出发设计了针对积分环节的控制规则库;引进Lyapunov函数,设计了输入隶属度函数论域值的自适应律和输出隶属度函数中心取值的自适应律,最后针对Duffing非线性系统仿真,结果表明设计的变论域模糊控制器是可行的。     

模糊值函数分析学的结构元方法简介(Ⅱ)——模糊值函数及微积分的结构元表述

介绍了利用模糊结构元的模糊值函数的解析表达形式及隶属函数确定,以及基于结构元表示的模糊值函数的微分与黎曼积分的定义、计算与部分性质.同时介绍了模糊值函数拟合的基本思想.     

遗传算法在自动泊车辅助系统模糊控制中的应用

随着汽车工业的发展,自动泊车辅助系统已逐渐成为汽车的必备装置.对自动泊车控制过程进行了分析,设计了自动泊车辅助系统模糊控制器,并将遗传算法应用于模糊控制器参数寻优过程,较为有效的确定了模糊控制器的参数,使用遗传算法工具箱对模糊控制器的隶属度函数进行了优化.并在Matlab环境下,对自动泊车模糊控制进行了仿真研究,论述了遗传算法在改善模糊控制效果中的应用.     

模糊合作博弈Shapley值的模糊结构元表示

将模糊数学理论应用到合作博弈中,用精确的数学表达式来表示实际生活中的模糊事件,又将模糊结构元理论应用到模糊合作博弈中,将模型中的模糊数用模糊结构元表示,以往基于扩张原理的模糊Shapley值的隶属函数非常复杂,本文给出其求解方法,使其得到解析表达.通过一个算例,来说明该模型的具体应用,与支付函数用区间数表示等研究方法相比较,该模型不仅保证了隶属函数的连续性,还给出区间上每个取值的隶属度,可以为管理者提供更精确的信息.     

模糊排队隶属函数的模糊结构元法

应用模糊结构元原理,研究了到达率和服务率均为模糊数的单列模糊排队问题,给出了系统特征值隶属函数的求解方法,避免了利用a-截集的定义和Zadeh的扩展原理方法带来的运算困难.实例分析了某售票系统的模糊排队问题,其中,顾客的平均到达率和系统的平均服务率均用模糊结构元表示,求解出了顾客平均等待时间的隶属函数的解析表示,说明了模糊结构元方法的优越性,同时为决策者提供了更加丰富的信息.     

基于结构元理论的模糊数的贴近度

现有的计算贴近度的方法,都是建立在模糊集合的隶属函数基础之上的.在很多情况下,当隶属函数很难解析表达时,这时就很难用这些方法计算贴近度.为此,在结构元理论的基础上,提出并构造了模糊数的贴近度(称之为元贴近度).当隶属函数很难解析表达时,用其他方法无法得到的贴近度,此时,用元贴近度的方法往往可以得到,并且计算非常简捷.最后,通过一个模式识别例子,表明该方法的有效性.     

基于贝塞尔曲线理论的备件需求模糊隶属度函数构建模型

用模糊理论描述备件需求是一种科学适用的方法,针对现有模糊变量隶属度函数构建方法的不足, 设计了基于贝塞尔曲线理论的备件需求模糊隶属度函数构建方法,给出了隶属度求解算法,分析了使拟合误差最小的控制点选择方法.同时通过实例验证以及与最小二乘法的对比分析,验证了贝塞尔曲线方法在构建备件需求模糊隶属度函数方面的有效性.此方法无需事先假设隶属度函数的形态,简单易用、使用灵活并且精度较高.     

基于模糊数学理论的沥青路面结构可靠度分析

在分析沥青路面结构可靠度时,为了更符合路面实际工况,将模糊数学理论纳入可靠度分析中.首先给出沥青路面结构的失效隶属函数;然后将路表弯沉值作为控制指标;从而推导出沥青路面结构模糊可靠度计算模式;并结合西咸新区二级沥青路段进行了相关的验证.结果表明:在一模糊事件中,模糊可靠度与传统可靠度相比总是低于传统可靠度.基于此,在对路面结构进行可靠性设计时采用模糊可靠度能更加巩固路面的使用性能,延长了路面的使用年限.在使用过程当中,外界因素对路面的损害程度相较于采用传统可靠度设计的路面结构小,从而使得路面的维修次数减少,节省了后期路面维护的人力和财力.所选取的隶属函数中k的取值和模糊临界区间均对模糊可靠度的大小起直接影响作用,通过对不同路面组合,不同k值的计算发现,当k值取作800σ_Z~(-2)~1 800σ_Z~(-2)较为合理.在具体的工程实践中,应该根据实际情况来确定临界区间的范围,以保证结构的安全性.     

Fractional programming approach to fuzzy weighted average

This paper proposes a fractional programming approach to construct the membership function for fuzzy weighted average. Based on the -cut representation of fuzzy sets and the extension principle, a pair of fractional programs is formulated to find the -cut of fuzzy weighted average. Owing to the special structure of the fractional programs, in most cases, the optimal solution can be found analytically. Consequently, the exact form of the membership function can be derived by taking the inverse function of the -cut. For other cases, a discrete but exact solution to fuzzy weighted average is provided via an efficient solution method. Examples are given for illustration.     

基于可变模糊集理论的城市用地适用性评估

依据可变模糊集理论,构造了城市用地适用性评估的相对差异函数模型和相对隶属函数模型,建立了求解综合相对隶属度的可变模糊评估模型,并应用该模型对2组待开发利用用地适用性进行了评估.研究表明:可变模糊评估是依据对立相对隶属函数来描述模糊概念,通过参数的可变性,自我验证可变模糊评估方法的可靠性,并通过级别特征值表达了评估对象属于某级别的程度,使评估结果更为精细,从而为城市用地适用性评估提供了一种有效的新方法.     

小波分析与模糊系统分析的联系

讨论小波基函数与模糊集隶属函数之间的联系 ,证明模糊系统研究与应用中的隶属函数都可以由称之为简单小波的母函数表出 ,反之每一简单小波也可以由某一隶属函数表出 ,从而验证简单小波类与某一隶属函数类的一一对应关系。该结果进一步揭示模糊推理和模糊控制的实质 ,为在模糊系统辨识、模糊控制和模糊数据分析等诸多领域充分利用近代小波分析的成果提供新思路     

Interval optimization based line sampling method for fuzzy and random reliability analysis

For structural system with fuzzy variables as well as random variables, a novel algorithm for obtaining membership function of fuzzy reliability is presented on interval optimization based Line Sampling (LS) method. In the presented algorithm, the value domain of the fuzzy variables under the given membership level is firstly obtained according to their membership functions. Then, in the value domain of the fuzzy variables, bounds of reliability of the structure are obtained by the nesting analysis of the interval optimization, which is performed by modern heuristic methods, and reliability analysis, which is achieved by the LS method in the reduced space of the random variables. In this way the uncertainties of the input variables are propagated to the safety measurement of the structure, and the membership function of the fuzzy reliability is obtained. The presented algorithm not only inherits the advantage of the direct Monte Carlo method in propagating and distinguishing the fuzzy and random uncertainties, but also can improve the computational efficiency tremendously in case of acceptable precision. Several examples are used to illustrate the advantages of the presented algorithm.     

Multicriteria Decision-making Method Based on Risk Attitude under Interval-valued Intuitionistic Fuzzy Environment

Based on the feature of interval-valued intuitionistic fuzzy multi-attribute decision-making, in this thesis, a mentality parameter is used to reflect the decision makers’ risk attitude in determining of both a membership degree and a non-membership degree. Besides, with the mentality parameter, a new score function and accuracy function are proposed, which integrate the membership degree, the non-membership degree and the hesitancy degree into one index. Furthermore, to compare two interval-valued intuitionistic fuzzy numbers, a new ranking method is generated with the score function and accuracy function. Finally, a multi-attribute decision method under interval-valued intuitionistic fuzzy environment is developed in a linear weighted average operator. And promising numerical results show that this method is available.     

Least-squares estimates in fuzzy regression analysis

Regression is a very powerful methodology for forecasting, which is considered as an essential component of successful OR applications. In this paper an idea stemmed from the classical least squares is proposed to handle fuzzy observations in regression analysis. Based on the extension principle, the membership function of the sum of squared errors is constructed. The fuzzy sum of squared errors is a function of the regression coefficients to be determined, which can be minimized via a nonlinear program formulated under the structure of the Chen–Klein method for ranking fuzzy numbers. To illustrate how the proposed method is applied, three cases, one crisp input-fuzzy output, one fuzzy input-fuzzy output, and one non-triangular fuzzy observations, are exemplified. The results show that the least-squares method of this paper is able to determine the regression coefficients with better explanatory power. Most important, it works for all types of fuzzy observations, not restricted to the triangular one.     

基于模糊中值滤波的椒盐噪声去除方法

研究基于模糊中值滤波的椒盐噪声去除方法。通过比较图像各像素点的灰度值,定义基于图像梯度信息的各点被判别为噪声点的模糊隶属函数。利用此模糊隶属函数对中值滤波方法进行加权,得到了一种加权中值滤波器,可实现边缘处椒盐噪声的有效滤除。讨论这种模糊加权方法与其它先进滤波方法的结合途径,指出了其推广应用价值。最后利用数值实验验证本文方法的有效性,结果表明,相比于自适应中值滤波方法,本文方法得到的滤波图像在峰值信噪比及结构相似度方面均有明显提高。     

Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision-making process

Pythagorean fuzzy set, an extension of the intuitionistic fuzzy set which relax the condition of sum of their membership function to square sum of its membership functions is less than one. Under these environment and by incorporating the idea of the confidence levels of each Pythagorean fuzzy number, the present study investigated a new averaging and geometric operators namely confidence Pythagorean fuzzy weighted and ordered weighted operators along with their some desired properties. Based on its, a multi criteria decision-making method has been proposed and illustrated with an example for showing the validity and effectiveness of it. A computed results are compared with the aid of existing results.     

基于模糊综合评判方法的土壤重金属污染度研究

本文应用模糊综合评判方法对城区的土壤污染情况进行评估,根据土壤重金属污染等级标准,确定隶属度函数的类型,并把土壤污染分为低污染、中等污染和高污染三个级别。按照隶属度最大的原则,确定各功能区样本点的污染级别,进而对各功能区的污染情况进行分析。