一类复杂非线性系统的模糊控制

针对一类复杂非线性系统,把模糊T-S模型和自适应模糊逻辑系统结合起来,提出了一种跟踪控制方案.首先,应用模糊T-S模型对非线性系统建模,设计观测器用来观测系统状态:其次,应用基于权值、中心和宽度3个参数可调节的自适应时延模糊逻辑系统补偿器来消除建模误差和小确定性.文中证明了闭环系统满足期望的跟踪性能.示例仿真结果表明了该方案的有效性.     

An optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty using genetic algorithms

This paper proposes an optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty (FOU) of the membership functions, considering three different cases to reduce the complexity problem of searching the parameter space of solutions. For the optimization method, we propose the use of a genetic algorithm (GA) to optimize the type-2 fuzzy inference systems, considering different cases for changing the level of uncertainty of the membership functions to reach the optimal solution at the end.     

Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic

Uncertainty is an inherent part in control systems used in real world applications. The use of new methods for handling incomplete information is of fundamental importance. Type-1 fuzzy sets used in conventional fuzzy systems cannot fully handle the uncertainties present in control systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us with more parameters and more design degrees of freedom. This paper deals with the design of control systems using type-2 fuzzy logic for minimizing the effects of uncertainty produced by the instrumentation elements, environmental noise, etc. The experimental results are divided in two classes, in the first class, simulations of a feedback control system for a non-linear plant using type-1 and type-2 fuzzy logic controllers are presented; a comparative analysis of the systems’ response in both cases was performed, with and without the presence of uncertainty. For the second class, a non-linear identification problem for time-series prediction is presented. Based on the experimental results the conclusion is that the best results are obtained using type-2 fuzzy systems.     

II型模糊控制综述

Ⅱ型模糊集合是传统Ⅰ型模糊集合的扩展,其特征是隶属度值本身为模糊集合.基于Ⅱ型模糊集合的Ⅱ型模糊控制器可以同时有效地处理语言和数据不确定性,在高小确定场合具有明显超过相应Ⅰ型控制器的性能表现.本文首先对Ⅱ型模糊集合及系统理论进行了概述,然后对Ⅱ型非自适应模糊控制器Ⅱ型自适应模糊控制器和Ⅱ型自组织模糊控制器的研究进展分别...     

不确定性推理技术在医学诊断中的应用研究

介绍了不确定性推理技术中几种主要方法,根据不同医学诊断的特点,设计了基于动态模糊逻辑和加权模糊逻辑相结合的计算机辅助医学诊断系统,最后通过一个实例说明了该方法的有效性。     

模糊逻辑技术在医学诊断中的应用研究

介绍了不确定性推理技术中几种主要方法,并分析了各种方法的优缺点。根据目前医学诊断中存在的问题及不同医学诊断的各自特点,设计了基于模糊逻辑的计算机辅助医学诊断系统,主要介绍了其中采用的动态模糊逻辑和加权模糊逻辑相结合的方法。该方法不仅能够帮助医生初步确诊疾病,而且能够分析出引起某种疾病变化的主要原因,从而帮助医生提高业务水平,提高其诊断的速度,减少误诊率。     

Information systems and uncertainty: a conspiracy of misplaced confidence

Abstract. Information technology is becoming an increasingly important factor in contemporary management. Information systems are being set up in business explicitly to accommodate the new opportunities of this technology, and these are having a lasting effect on managerial practice. The full implications of this technology-driven development have not been appreciated by organizations, which in absorbing technological systems, are tolerating a great drain on their resources.
The efficacy of computers is predicated on the acceptance of some very specific perspectives. A growing discontent and disappointment with their limited achievements is our reason for advocating a different point of view. We will discuss how a shift in perspective, particularly in respect to the perception of uncertainty, will affect thinking and practice in the field of management support systems. We will render our view of the application of computerized decision support systems (DSS), and especially, we will focus on the beliefs and assumptions that have shaped this technology thus far. To this end we will discuss the concept of uncertainty, by juxtaposing current thinking and practice with our understanding of the context of its application. Finally, we will place our understanding of uncertainty in a managerial context and explain the implications this would have for strategists.     

Fuzzy Logic for Biological and Agricultural Systems

Fuzzy logic is a powerful concept for handling non-linear, time-varying, adaptive systems. It permits the use of linguistic values of variables and imprecise relationships for modeling system behavior. The paper presents an overview of fuzzy logic modeling techniques, its applications to biological and agricultural systems and an example showing the steps of constructing a fuzzy logic model.     

基于模糊逼近的一类不确定非线性系统的容错控制

针对一类不确定非线性系统,提出了一种模糊容错控制方案.采用模糊T-S模型来逼近非线性系统,由线性矩阵不等式设计模糊模型的控制律.构建了模糊逻辑系统作为补偿器来抵消对非线性系统的建模误差和因故障引起的不确定性,并证明了闭环系统能够满足期望的跟踪性能.仿真实例表明了所提出容错控制方案的有效性.     

支持模糊粗糙本体的推理机研究

不精确信息进行表达和推理逐渐成为一种必然的需求,而经典的本体并不适合处理这种不确定的信息.设计了一种支持模糊粗糙本体的推理机,其最大的特点是处理的对象是模糊粗糙本体,从而解决了不确定信息的推理问题.对模糊粗糙本体模型进行了研究,着重介绍了该模糊粗糙本体推理机的总体结构、功能及推理机中各模块的作用,通过对模糊粗糙本体进行约简和去粗糙处理,最终将对模糊粗糙本体的推理转化为经典的推理.     

加权模糊逻辑

文中提出了一种加权模糊逻辑推理模型，该模型描述了不确定性问题求争领域中的比较普遍存在的“加权逻辑与”“加权逻辑或”和“加权逻辑综合”等模糊逻辑关系，该推理模型在国家“八六三”高技术项目“吉林省玉米生产智能化信息技术示范工程”中进行了应用。文中同间指出对３种加权模糊之间的关系，与３种加权模糊逻辑运算的相关的真值计算方法，以及３种真值计算方法之间的关系等作应进一步研究。     

Fuzzy Non-Homogeneous Markov Systems

In this paper the theory of fuzzy logic and fuzzy reasoning is combined with the theory of Markov systems and the concept of a fuzzy non-homogeneous Markov system is introduced for the first time. This is an effort to deal with the uncertainty introduced in the estimation of the transition probabilities and the input probabilities in Markov systems. The asymptotic behaviour of the fuzzy Markov system and its asymptotic variability is considered and given in closed analytic form. Moreover, the asymptotically attainable structures of the system are estimated also in a closed analytic form under some realistic assumptions. The importance of this result lies in the fact that in most cases the traditional methods for estimating the probabilities can not be used due to lack of data and measurement errors. The introduction of fuzzy logic into Markov systems represents a powerful tool for taking advantage of the symbolic knowledge that the experts of the systems possess.     

基于模糊积分的客户分类不确定性优化研究

数据挖掘技术为高效的客户分类提供了强大的支持,然而仅依靠这门技术并不能很好地完成这项任务。因为分类方法的局限性,现实数据存在信息的不确定、不完整、先验知识缺乏,研究对象的复杂性等困难导致的分类不确定性。从这个角度出发,将模糊积分融合方法与数据挖掘技术结合来减小客户分类的不确定性,提出了一种模糊密度修正方法,它利用了训练样本先验静态信息和各分类器识别结果包含的动态信息对模糊密度进行自适应动态赋值。仿真结果表明了它的有效性。     

不确定非线性系统的模糊鲁棒??∞ 跟踪控制

针对一类不确定非线性系统,提出一种新的模糊鲁棒H∞跟踪控制方案。应用模糊T-S模型表征非线性系统,系统不确定性通过模糊逻辑系统消除。由线性矩阵不等式和自适应律给出了模糊控制器存在的一个充分条件。基于Lyapunov稳定性理论,模糊控制方案在所有闭环信号最终一致有界下保证了期望的H∞跟踪性能。两连杆机械臂的仿真结果表明了该方案的可行性。     

不确定性操作臂的混合模糊P+ID控制的实验研究

提出了一种机械臂的混合模糊控制策略,它由一企增量模糊逻辑控制器和传统的积分－微分管制器构成,简称ＰｕｚｚｙＰ＋ＩＤ控制器,与传统的ＰＩＤ控制器相比,设计ＦｕｚｚｙＰ＋ＩＤ控制器时,只需多调节一个附加参数,我们应用ＦｕｚｚｙＰ＋ＩＤ控制器控制几何参数变化的两连杆机构臂ＥＤＤＡ,ＥＤＤＡ的阶跃和跟踪控制的实验结果表明：ＦｕｚｚｙＰ＋ＩＤ控制器更有效和更鲁棒。     

Fuzzy operator logic and fuzzy resolution

There have been only few attempts to extend fuzzy logic to automated theorem proving. In particular, the applicability of the resolution principle to fuzzy logic has been little examined. The approaches that have been suggested in the literature, however, have made some semantic assumptions which resulted in limitations and inflexibilities of the inference mechanism. In this paper we present a new approach to fuzzy logic and reasoning under uncertainty using the resolution principle based on a new operator, the fuzzy operator. We present the fuzzy resolution principle for this logic and show its completeness as an inference rule.     

面向后件集的模糊推理机制: 用于区间型type-2模糊逻辑系统

目前,大多数模糊推理都是利用t-范数和t-余范数或其改进形式对连接词进行建模,这些模型不能将模糊规则中前件集与后件集之间的相关性信息引入到模糊推理过程,这会丢失蕴含在规则中的一些信息甚至导致推理结果与实际经验严重不符.为解决此问题,本文首先引入模糊集合面向对象变换的概念,并将其推广,建立了合成type-2模糊集合模型.基于此模型,针对区间型type-2模糊逻辑系统,提出一种面向后件集的模糊推理机制,该机制能将前件集与后件集的相关性信息(包括清晰数和模糊数两种情形)引入到模糊推理过程.仿真结果表明,该方法能捕获到模糊规则中更多的不确定性信息,并为模糊逻辑系统的设计提供更大的自由度.     

基于T-S模型的锌钡白干燥煅烧过程自适应神经模糊推理系统建模

针对锌钡白干燥煅烧过程建模难的问题，提出了一种基于T-S模型的自适应神经模糊推理系统(ANFIS)建模方法．通过对模糊辨识系统的结构辨识和参数辨识，使网络自主、迅速地收敛到要求的输入输出关系．文章讨论了该网络的结构和学习算法，并通过仿真研究得出其良好的实际应用价值．