带模糊参数的系统模糊可靠度分析

含模糊参数系统的可靠性理论研究具有广泛的实际应用背景,但由于模糊数运算的隶属函数表达困难,影响和制约着模糊参数系统的模糊可靠性理论与应用的研究。本文利用模糊数的结构元表示,给出了模糊表达式隶属函数确定的两种方法,进而得到了具有模糊参数的不可修复串联和并联系统模糊可靠度的隶属函数表达式。     

基于模糊双线性模型的非线性系统的跟踪控制

研究一种基于T-S模糊双线性系统的跟踪控制器设计及稳定性分析.使用分布并行补偿法(PDC)设计了模糊控制器,得到模糊双线性系统跟踪控制渐近稳定的充分条件,仿真结果验证了该方法改进了闭环系统的性能.     

模糊输入时滞系统的输出反馈控制及稳定性分析

针对一类状态不可测的模糊输入时滞系统,应用平行分布补偿算法(PDC),设计了模糊观测器,提出了基于模糊观测器的输出反馈控制方法,给出了保证模糊时滞系统渐近稳定的新的充分条件.应用广义Lyapunov函数和线性矩阵不等式方法,证明了模糊输入时滞系统的渐近稳定性,同时给出了控制和观测增益矩阵的分离设计算法.仿真结果进一步验证了所提出的方法和条件的有效性.     

Rule generation for hierarchical collaborative fuzzy system

A new method of rule generation for the hierarchical collaborative fuzzy system, HCFS, is proposed. This HCFS is structured like various parallel fuzzy subsystems and it overcomes the dimensionality problem and the lack of interpretability of most of the traditional fuzzy systems, when dealing with complex real-world problems. An association process of different fuzzy systems is presented in this work, through the use of a relevance concept of a fuzzy system. The result of this aggregation is a collaborative structure where all sub-models have the ability to gradually improve the overall accuracy of approximation by adding their own contributions. For this structure we propose a new algorithm to be used in the procedures of the three learning phases: the structure building, the parametric identification and the division of the learning data among the various levels of the hierarchical structure. This new fuzzy modelling technique automatically generates and tunes the sets of fuzzy rules in the hierarchical collaborative structure (HCS). The effectiveness of the proposed HCFS model in handling high-dimensional and complex problems is demonstrated through various numerical simulations.     

Tracking a near-field moving target using fuzzy neural networks

In this paper we explore the problem of tracking a near-field moving target using fuzzy neural networks (FNNs). The moving target radiates narrow band waves that impinge on an array of passive sensors. At a particular time instance, the location of the target is estimated by several judiciously constructed FNN-based angle and distance estimators. When the target is moving, its trajectory can be on-line estimated due to the parallel and real-time computational capability of the FNNs. Computer simulation results illustrate the performance of the FNN-based angle estimator, distance estimator, and the near-field moving target tracker.     

Fuzzy power sets and fuzzy implication operators

The theory of fuzzy power sets, which has hitherto been insufficiently developed, is shown very naturally to require the use of a fuzzy implication operator (Section 1). Six such operators are gathered from the literature on multiple-valued logic (Section 2), and their effects on fuzzy power-set theory are compared throughout the rest of the paper. After certain fundamental definitions of set characteristics (Section 3), the six operators are carried in parallel while working out basic aspects of power-set theory. Among these are the properties of the set-inclusion relation and the set-equivalence relation (Section 4), two distinct concepts of disjointness (Section 5), questions of consistency in the relations between a set and its complement (Section 6), and a very concrete theorem on a difference among the operators with regard to the derivation of crisp conclusions from fuzzy premises (Section 7). Finally (Section 8), emphasis is placed on the dependence of the choice of operators upon the purposes the user has in hand.     

模糊逻辑语言FLL的并行计算模型FPCM

该文在研究模糊逻辑语言ＦＬＬ 语义的基础上,提出了并行计算模型ＦＰＣＭ（ＦｕｚｚｙＰａｒａｌｌｅｌ ＣｏｍｐｕｔｅＭｏｄｅｌ）．该模型描述了模糊逻辑程序设计语言ＦＬＬ 的并行计算结构,以此实现了“ＡＮＤ 并行”和“ＯＲ 并行”计算,并利用所提出的警卫条件、计算负影响等机制进一步提高了ＦＬＬ 语言的并行执行效率,从而有效地解决了模糊逻辑语言执行效率低的问题．     

Long-range predictive adaptive fuzzy relational control

A class of long-range predictive adaptive fuzzy relational controllers is presented. The plant behavior is described over an extended time horizon by a fuzzy relational model which is identified based on input-output closed-loop observations of the plant variables. In this class of adaptive controllers the control law attempts to minimize a quadratic cost over an extended control horizon. When used with linear models, this approach has revealed a significant potential for overcoming the limitations of one-step ahead schemes, such as the stabilization of non-minimum phase plants. Here, a uniform framework is adopted for implementing both the fuzzy model and the fuzzy controller, namely distributed fuzzy relational structures gaining from their massive parallel processing features and from the learning capabilities typical of the connectivist approaches. Issues such as maintenance during the adaptation process of the meaning of linguistic terms used at both fuzzy systems interfaces are addressed, namely by introducing a new design methodology for on-line fuzzy systems interface adaptation. The examples presented reinforce the claim of the usefulness of this new approach.     

The Further Study of Safety Stock under Uncertain Environment

Corresponding to stochastic variable, it is a better choice to describe the market demand uncertainty of innovative products with fuzzy variable because no historical data is available. Traditionally, possibility measure is regarded as the parallel concept of probability measure. However, it is, in fact, the credibility measure that plays the role of probability measure! Based on the credibility theory, this paper studies how to evaluate the safety stock of enterprise given desired product availability when the node enterprise market demand of supply chain is described by Gauss fuzzy variable. Thereinafter, the authors discuss the impact of required product availability and demand uncertainty on safety stock, compare the correlative issues with stochastic demand, and get some useful results.     

A heuristic method for RCPSP with fuzzy activity times

In this paper, we propose a heuristic method for resource constrained project scheduling problem with fuzzy activity times. This method is based on priority rule for parallel schedule generation scheme. Calculation of critical path in this case requires comparison of fuzzy numbers. Distance based ranking of fuzzy number is used for finding the critical path length and concept of shifting criticality is proposed for some of the special cases. We also propose a measure for finding the non-integer power of a fuzzy number. We discuss some properties of the proposed method. We use an example to illustrate the method.     

FRACTOP: A Geometric Partitioning Metaheuristic for Global Optimization

We propose a new metaheuristic, FRACTOP, for global optimization. FRACTOP is based on the geometric partitioning of the feasible region so that search metaheuristics such as Simulated Annealing (SA), or Genetic Algorithms (GA) which are activated in smaller subregions, have increased reliability in locating the global optimum. FRACTOP is able to incorporate any search heuristic devised for global optimization. The main contribution of FRACTOP is that it provides an intelligent guidance (through fuzzy measures) in locating the subregion containing the global optimum solution for the search heuristics imbedded in it. By executing the search in nonoverlapping subregions, FRACTOP eliminates the repetitive visits of the search heuristics to the same local area and furthermore, it becomes amenable for parallel processing. As FRACTOP conducts the search deeper into smaller subregions, many unpromising subregions are discarded from the feasible region. Thus, the initial feasible region gains a fractal structure with many space gaps which economizes on computation time. Computational experiments with FRACTOP indicate that the metaheuristic improves significantly the results obtained by random search (RS), SA and GA.     

模糊不确定时滞系统的保成本控制

讨论了基于T-S模型的不确定时滞系统的保成本控制问题.文章采用并行补偿状态反馈控制方法和时滞相关稳定性分析方法,通过引入一个带调节因子的Lyapunov-Krasovskii泛函,利用线性矩阵不等式的形式给出了状态反馈控制器存在的充分条件.当调节因子取不同值时,最小保成本值和反馈增益也是不同的,不同的反馈增益导致不同的动态性能,因此,可以通过选取合适的调节因子来优化闭环系统的动态性能. 最小保成本值可以看作调节因子的函数,因此,可以通过求解一个凸优化问题来求得最小的保成本值和最优的调节因子,文章给出了一个求解最小保成本值的算法.并利用仿真示例验证了所给方法的有效性.     

Identification of fuzzy relation models using hierarchical fair competition-based parallel genetic algorithms and information granulation

The paper is concerned with a hybrid optimization of fuzzy inference systems based on hierarchical fair competition-based parallel genetic algorithms (HFCGA) and information granulation. The process of information granulation is realized with the aid of the C-Means clustering. HFCGA being a multi-population based parallel genetic algorithms (PGA) is exploited here to realize structure optimization and carry out parameter estimation of the fuzzy models. The HFCGA becomes helpful in the context of fuzzy models as it restricts a premature convergence encountered quite often in optimization problems. It concerns a set of parameters of the model including among others the number of input variables to be used, a specific subset of input variables, and the number of membership functions. In the hybrid optimization process, two general optimization mechanisms are explored. The structural development of the fuzzy model is realized via the HFCGA optimization and C-Means, whereas to deal with the parametric optimization we proceed with a standard least square method and the use of the HFCGA technique. A suite of comparative studies demonstrates that the proposed algorithm leads to the models whose performance is superior in comparison with some other constructs commonly used in fuzzy modeling.     

Editorial

Linear programming problems with fuzzy parameters are formulated by fuzzy functions. The ambiguity considered here is not randomness, but fuzziness which is associated with the lack of a sharp transition from membership to nonmembership. Parameters on constraint and objective functions are given by fuzzy numbers. In this paper, our object is the formulation of a fuzzy linear programming problem to obtain a reasonable solution under consideration of the ambiguity of parameters. This fuzzy linear programming problem with fuzzy numbers can be regarded as a model of decision problems where human estimation is influential.     

一类不确定非线性系统的执行器故障模糊容错控制

针对一类状态不完全可测的不确定非线性系统,研究了带有执行器故障的容错控制问题.采用 T-S模型对非线性系统进行模糊建模,利用并行分布补偿(PDC)算法设计了状态现潮器和基于状态现 潮器的客错控制,给出了保证该模糊容错控制系统稳定的充分条件.根据李雅普诺夫稳定性理论和线性 矩阵不等式(LMI),证明了所提出的模糊容错控制方法不但使得模糊控制系统渐近稳定,而且能够取得 H∞性能指标.计算机仿真结果进一步验证了所提出方法的正确性.     

A New Form of Fuzzy Compact Spaces and Related Topics via Fuzzy Idealization

Fuzzy ideals and the notion of fuzzy local function were introduced and studied by Sarkar[12] and by Mahmoud in [9]. The purpose of this paper deals with a fuzzy compactness modulo a fuzzy ideal. Many new sorts of weak and strong fuzzy compactness have been introduced to fuzzy topological spaces in the last twenty years but not have been studied using fuzzy ideals so,the main aim of our work in this paper is to define and study some new various types of fuzzy compactness with respect to fuzzy ideals namely fuzzy L-compact and L*-compact spaces. Also fuzzy compactness with respect to ideal is useful as unification and generalization of several others widely studied concepts. Possible application to superstrings and E∞ space-time are touched upon.     

Bi-matrix Games with Fuzzy Goals and Fuzzy

A bi-matrix game with fuzzy goal is shown to be equivalent to a (crisp) non-linear programming problem in which the objective as well as all constraint functions are linear except two constraint functions, which are quadratic. This equivalence is further extended to bi-matrix games with fuzzy pay-offs, as well as to bi-matrix games with fuzzy goals and fuzzy payoffs, whose equilibrium strategies are conceptualized by employing a suitable ranking (defuzzification) function.     

Toward extended fuzzy logic—A first step

Fuzzy logic adds to bivalent logic an important capability—a capability to reason precisely with imperfect information. Imperfect information is information which in one or more respects is imprecise, uncertain, incomplete, unreliable, vague or partially true. In fuzzy logic, results of reasoning are expected to be provably valid, or p-valid for short. Extended fuzzy logic adds an equally important capability—a capability to reason imprecisely with imperfect information. This capability comes into play when precise reasoning is infeasible, excessively costly or unneeded. In extended fuzzy logic, p-validity of results is desirable but not required. What is admissible is a mode of reasoning which is fuzzily valid, or f-valid for short. Actually, much of everyday human reasoning is f-valid reasoning.f-Valid reasoning falls within the province of what may be called unprecisiated fuzzy logic, FLu. FLu is the logic which underlies what is referred to as f-geometry. In f-geometry, geometric figures are drawn by hand with a spray pen—a miniaturized spray can. In Euclidean geometry, a crisp concept, C, corresponds to a fuzzy concept, f-C, in f-geometry. f-C is referred to as an f-transform of C, with C serving as the prototype of f-C. f-C may be interpreted as the result of execution of the instructions: Draw C by hand with a spray pen. Thus, in f-geometry we have f-points, f-lines, f-triangles, f-circles, etc. In addition, we have f-transforms of higher-level concepts: f-parallel, f-similar, f-axiom, f-definition, f-theorem, etc. In f-geometry, p-valid reasoning does not apply. Basically, f-geometry may be viewed as an f-transform of Euclidean geometry.What is important to note is that f-valid reasoning based on a realistic model may be more useful than p-valid reasoning based on an unrealistic model.     

Fuzzy addition in the L-fuzzy real line

Under the hypothesis L is a chain, we construct a binary operation ⊕ on the L-fuzzy real line $\text{R}$(L) which reduces to the usual addition on $\text{R}$ if ⊕ is restricted to the embedded image of $\text{R}$ in $\text{R}$(L), which yields a partially ordered, abelian cancellation semigroup with identity, and which is jointly fuzzy continuous on $\text{R}$(L). We show ⊕ is unique, i.e. it is the only extension of addition to $\text{R}$(L) which is consistent. We study the relationship between ⊕ and other fuzzy continuous extensions of the usual addition. We also show that fuzzy translation is a weak fuzzy homeomorphism and, under certain conditions, a fuzzy homeomorphism.     

Fuzzy压缩原理

本文给出以Ｆｕｚｚｙ数作为Ｌｉｐｓｃｈｉｔｚ常数的压缩映射的新概念，并成功证明了Ｆｕｚｚｙ数值函数的不动点定理。