室内热舒适环境的模糊关系矩阵模型控制系统

针对复杂非线性系统中多个输出不能解耦的控制问题,基于实际系统的采样数据,利用矩阵半张量积运算建立模糊关系矩阵模型,得出一种新型模糊控制器设计方法.将传统模糊控制中的推理过程和模糊规则的建立转化成矩阵运算,有效避免了建模和控制的复杂性.将其应用于室内热环境舒适度控制系统中,基于室内外的温度、湿度等多个变量的采样数据对,给出具体的模糊关系矩阵的建立过程,设计得出新型模糊控制器.仿真和实验结果表明,该方法能够实现室内热环境的舒适度控制,并且不需要进行多变量之间的解耦.     

积模糊粗集模型及其模糊知识粒的表示和分解

为处理人工智能中不精确和不确定的数据和知识,Pawlak提出了粗集理论。之后粗集理论被推广,其方法主要有二:一是减弱对等价关系的依赖;二是把研究问题的论域从一个拓展到多个。结合这两种思想,研究基于两个模糊近似空间的积模糊粗集模型及其模糊粗糙集的表示和分解。根据这种思想,可以从论域分解的角度探索降低高维模糊粗糙集计算的复杂度问题。先对模糊近似空间的分层递阶结构———λ-截近似空间进行研究,得到不同层次知识粒的相互关系;然后定义模糊等价关系的积,并研究其性质及算法;最后构建基于积模糊等价关系的积模糊粗集模型,并讨论了该模型中模糊粗糙集的表示及分解问题,分别从λ-截近似空间和一维模糊近似空间的角度去处理,给出了可分解集的上(下)近似的一个刻画,及模糊可分解集的上(下)近似的λ-截集分解算法。     

基于优势-直觉模糊粗糙模型的IT项目绩效审计评价规则获取

针对我国政府审计机关对政府投资的I`I}项目进行绩效审计评价规则知识获取的困难,考虑了条件属性取值 为优势精确值、分类结果为直觉模糊值的决策系统规则获取问题。首先比较条件属性值的大小,构建对象的优势部 域,再由对象邻域的直觉模糊值确定对象的上下近似;根据对象的上下近似和不同对象的直觉模糊值确定对象间的区 分关系,利用分辫矩阵给出知识约简和规则提取算法;最后将直觉模糊粗糙模型应用于政府I"I'项目绩效审计评价规 则的获取,得到了较为合理的IT项目绩效评价规则。     

基于优势关系下模糊目标信息系统的属性约简

在现实生活中,许多信息系统不仅是模糊的还是基于优势关系的。在基于优势关系下模糊目标信息系统中引入了广义决策的概念,提出了分别保持下广义决策、上广义决策、广义决策不变的三种不同约简,进一步给出了各属性约简的判定定理和辨识矩阵,提供了在优势关系下模糊目标信息系统属性约简的具体方法。通过实例验证了该方法的有效性,进一步丰富了粗糙集理论。     

二型模糊粗糙属性约简模型

属性约简是粗糙集理论的重要应用之一,其目的是在保持分类能力不变的前提下去掉冗余的属性,从而简化信息系统。由于经典粗糙集等价关系的要求过于严格,为了更好地解决实际问题,将粗糙集与二型模糊集结合,得到二型模糊粗糙集。利用论域和特征空间的积空间上的两个一型模糊集来构造论域的一个二型模糊划分,将模糊粗糙集属性约简的模型推广到二型模糊粗糙集框架中,得到了一个二型模糊粗糙属性约简的模型,并举例说明了用此模型进行属性约简的方法。     

Fuzzy quality function deployment: determining the distributions of effort dedicated to technical change

A model is presented that develops the Quality Function Deployment (QFD) House of Quality tool into a fuzzy‐set based multi‐criteria decision‐making process to determine the distributions of effort directed toward technical changes. When customers are polled for desired product‐specific attributes, the responses are typically defined by linguistic variables that represent a fuzzy set distribution. Fuzzy sets also define customer perceptions of the product attributes and technical expert opinions about product design criteria relative to marketplace competitors. Therefore, for each technical criterion, the following factors have an effect on the decision to implement change(s): (1) fuzzy sets providing evidence of customer need for attributes; (2) motivation to change to satisfy desired customer attributes; (3) motivation for technical criterion change; and (4) the strength of the relationships between the attributes and the technical criterion. Priority rankings are linked to the distributions of effort to apply in fulfilling continuous product improvement.     

风力发电机组的变论域自适应模糊控制

建立了变速变浆距风力发电机组的简化模型。在此基础上，将变论域自适应模糊控制应用到风力发电机组的转速和浆距控制系统中，改善风力发电机组的风能捕获性能。变论域自适应模糊控制器在保持规则形式不变的前提下。论域随着误差的变化而变化。这种控制器不但具有经典模糊控制的优点，如不需要精确的数学模型，产生非线性控制动作，良好的动态性能等．而且具有较高的控制精度。仿真结果证明该方法改善了风力发电机组的控制性能。     

模糊相容商空间与模糊子集

本文利用商空间理论中的粒度和层次概念来讨论模糊子集的结构和性质.首先将基于等价关系的商空间理论推广到基于模糊相容关系,接着讨论模糊相容关系的同构性及同构性的判别问题,最后利用模糊相容关系定义模糊子集,并讨论其性质.主要给出以下结果:(1)模糊相容关系的几种等价表示形式;(2)模糊相容关系的同构定义;(3)模糊相容关系同构的判别准则;(4)模糊相容关系下的模糊子集的定义及其相关性质;以及(5)模糊子集同构的充分必要条件.这些结果加深了我们对模糊相容关系和模糊集的理解.     

模糊近似空间上的粗糙模糊集的公理系统

粗糙集理论是近年来发展起来的一种有效的处理不精确、不确定、含糊信息的理论，在机器学习及数据挖掘等领域获得了成功的应用．粗糙集的公理系统是粗糙集理论与应用的基础．粗糙模糊集是粗糙集理论的自然的有意义的推广．作者研究了模糊近似空间上的粗糙模糊集的公理系统，用三条简洁的相互独立的公理完全刻划了模糊近似空间上的粗糙模糊集，同时还把作者给出的公理系统与粗糙集的公理系统做了对比，指出了两者的区别．     

一种模糊自适应温度控制系统的设计

介绍了一种以单片机为核心,采用变论域模糊控制算法的温度控制系统,并对模糊控制思想及系统的软、硬件设计进行了阐述。采用该控制系统,能较好地克服温度控制对象的纯滞后特性,控制响虚时间短,超调小,且适用范围广泛。     

Fuzzy rough set on probabilistic approximation space over two universes and its application to emergency decision‐making

Probabilistic approaches to rough sets are still an important issue in rough set theory. Although many studies have been written on this topic, they focus on approximating a crisp concept in the universe of discourse, with less effort on approximating a fuzzy concept in the universe of discourse. This article investigates the rough approximation of a fuzzy concept on a probabilistic approximation space over two universes. We first present the definition of a lower and upper approximation of a fuzzy set with respect to a probabilistic approximation space over two universes by defining the conditional probability of a fuzzy event. That is, we define the rough fuzzy set on a probabilistic approximation space over two universes. We then define the fuzzy probabilistic approximation over two universes by introducing a probability measure to the approximation space over two universes. Then, we establish the fuzzy rough set model on the probabilistic approximation space over two universes. Meanwhile, we study some properties of both rough fuzzy sets and fuzzy rough sets on the probabilistic approximation space over two universes. Also, we compare the proposed model with the existing models to show the superiority of the model given in this paper. Furthermore, we apply the fuzzy rough set on the probabilistic approximation over two universes to emergency decision‐making in unconventional emergency management. We establish an approach to online emergency decision‐making by using the fuzzy rough set model on the probabilistic approximation over two universes. Finally, we apply our approach to a numerical example of emergency decision‐making in order to illustrate the validity of the proposed method.     

一种典型二阶系统的模糊控制器的设计

介绍一种典型二阶系统的模糊控制器的设计方法。按照常规的步骤设计模糊控制器,在论域定义时采用一种新方法：根据未加入模糊控制器时,对应于系统模糊控制器输入、输出各个超调量的大小来设定模糊控制器的论域。实验仿真结果表明该设计方法能使系统达到较好的控制效果。     

基于三化设计的产品质量模糊综合评价

针对工程机械产品性能评定的多层次和多因素性,提出了应用模糊理论与产品设计方法相结合的多层次模糊综合评价模型。以新型液压振动沉拔桩机为例,利用基于三化综合设计法的产品质量模糊综合评价对其进行了产品质量综合评价,同时也对设计方法进行了评价与验证。通过此方法可以判定产品特性和等级,以及各产品在结构性能、工作性能与工艺性能三方面的性能差距,为评价与提高产品总体质量提供科学的决策依据。     

基于模糊积分的多模糊决策树融合

给定一个模糊信息系统,可能找到多个重要的模糊属性子集,而且这些重要的模糊属性子集对决策有不同的贡献,会产生不同的影响.如果仅选择其中一个模糊属性子集进行决策,即使是最重要的一个,也会丢失隐含在其他重要的模糊属性子集中的可用信息.为了充分利用模糊信息系统中每个重要的模糊属性子集所提供的信息,提出了一种基于模糊积分的多模糊决策树融合方法.这种方法分3个步骤：1)通过模糊等价关系找到几个重要的模糊属性子集;2)对每个模糊属性子集,利用模糊ID3算法生成一棵模糊决策树;3)用模糊积分融合几棵模糊决策树.实验结果证明了用多模糊决策树融合方法比单模糊决策树分类效果更好.     

加型Pythagorean模糊偏好关系的多属性决策方法

考虑Pythagorean模糊偏好关系的多属性决策问题,提出了加性Pythagorean模糊偏好关系的多属性决策方法。基于加性一致性Pythagorean模糊偏好关系提出一种新的Pythagorean模糊权重确定模型。给出了可接受加性一致性Pythagorean模糊偏好关系的定义,并针对不满足可接受加性一致性的Pythagorean模糊偏好关系,提出一种加性一致性调整算法。给出基于Pythagorean模糊偏好关系加性一致性的多属性决策方法,并通过实例分析提出的新方法的可行性和合理性。     

一种模糊区域的拓扑关系模型

空间区域拓扑关系建模是空间推理、地理信息系统(GIS)和计算机视觉等领域一个非常重要的主题，模糊区域的拓扑关系建模正日益受到相关领域研究者的重视，在分析现有模型的基础上，提出了一种模糊区域的拓扑关系模型，该模型利用模糊集来表示模糊区域，通过三个谓词的真值来判断区域间的拓扑关系，将分明区域作为特例统一处理，根据谓词的多种真值能够实现多层次上的拓扑关系分析．     

Generating indistinguishability operators from prototypes

Given a T‐indistinguishability operator E defined between some fuzzy subsets of a universe of discourse X, this paper studies three ways to generate an indistinguishability operator on X compatible with E inspired by the tools used in approximate reasoning and on the duality principle. Of special interest are the cases when the fuzzy subsets determine a partition and a hard‐partition of the universe X. © 2002 Wiley Periodicals, Inc.     

Quick Design of Fuzzy Controllers With Good Interpretability in Mobile Robotics

This paper presents a methodology for the design of fuzzy controllers with good interpretability in mobile robotics. It is composed of a technique to automatically generate a training data set plus an efficient algorithm to learn fuzzy controllers. The proposed approach obtains a highly interpretable knowledge base in a very reduced time, and the designer only has to define the number of membership functions and the universe of discourse of each variable, together with a scoring function. In addition, the learned fuzzy controllers are general because the training set is composed of a number of automatically generated examples that cover the universe of discourse of each variable uniformly and with a predefined precision. The methodology has been applied to the design of a wall-following and moving object following behavior. Several tests in simulated environments using the Nomad 200 robot software and a comparison with another learning method show the performance and advantages of the proposed approach.     

On Maximum Stability Margin Design of Nonlinear Uncertain Systems: Fuzzy Control Approach

This paper studies the maximum stability margin design for nonlinear uncertain systems using fuzzy control. First, the Takagi and Sugeno fuzzy model is employed to approximate a nonlinear uncertain system. Next, based on the fuzzy model, the maximum stability margin for a nonlinear uncertain system is studied to achieve as much tolerance of plant uncertainties as possible using a fuzzy control method. In the proposed fuzzy control method, the maximum stability margin design problem is parameterized in terms of a corresponding generalized eigenvalue problem (GEVP). For the case where state variables are unavailable, a fuzzy observer‐based control scheme is also proposed to deal with the maximum stability margin for nonlinear uncertain systems. Using a suboptimal approach, we characterize the maximum stability margin via fuzzy observer‐based control in terms of a linear matrix inequality problem (LMIP). The GEVP and LMIP can be solved very efficiently via convex optimization techniques. Simulation examples are given to illustrate the design procedure of the proposed method.