Z-Quantale及其范畴性质

本文把集系统的概念应用到Quantale理论中,作为Quantale的一般化,引入了Z-quantale的概念,研究了Z-quantale及其范畴的若干性质.主要结果有:证明了Z-quantale范畴是序半群范畴的反射子范畴,凝聚Z-quantale范畴是Z-quantale范畴的余反射子范畴.讨论了Z-quantale范畴中的投射对象,证明了Z-quantale A是E-投射的当且仅当它是稳定Z-连续的.     

L-fuzzy N-收敛空间

本文给出L-fuzzy N-收敛空间的定义,讨论L-fuzzy N-收敛空间范畴(L-fuzzyN-收敛空间和它们之间的连续映射构成的范畴)的若干范畴的性质,并且证明它的一个子范畴同构与L-fuzzy拓扑空间范畴.     

Fuzzy拓扑范畴的经典表示

构造范畴WPC，论证它与拓扑分子格范畴CDB等价；并在此基础上阐述经典拓扑范畴TOP是范畴WPC的满子范畴，为研究经典拓扑学与Fuzzy拓扑学之间联系提供一点思路。     

Koszul微分分次模

引入了Koszul微分分次模的概念. 给定Koszul微分分次代数上的一个下有界的微分分次模, 如果这个模到平凡模的Ext-\!群是有界的分次空间, 则它必定包含一个微分分次子模, 其在适当的截断和移位下是Koszul微分分次模; 这样的模还可以通过一系列Koszul微分分次模来逼近(参见本文推论3.6). 设$A$是一个Koszul微分分次代数, $D^c(A)$是微分分次右$A$-\!模范畴的导出范畴中由对象$A_A$生成的满三角子范畴. 如果平凡微分分次模$k_A$落在范畴$D^c(A)$中, 则三角范畴$D^c(A)$的标准$t$-\!结构的中心, 作为Abel范畴, 与某个有限维代数上的有限生成模范畴对偶. 进一步, 可推得三角范畴$D^c(A)$等价于它的标准$t$-\!结构的中心的有界导出范畴.     

L-fuzzy Locale理论与分配格的L-fuzzy拓扑表示

首先文中引入了Ｌ-ｆｕｚｚｙｌｏｃａｌｅ范畴，并证明了该范畴与满层Ｌ-ｆｕｚｚｙ拓扑空间范畴的关系类似于ｌｏｃａｌｅ与拓扑空间的联系．其次，文中建立了分配格的ｌｏｃａｌｅ式ｆｕｚｚｙＳｔｏｎｅ表示，并且与经典结果一致，任一分配格的Ｌ-ｆｕｚｚｙｌｏｃａｌｅ表示的点空间就是它的Ｌ-ｆｕｚｚｙ谱空间．     

辫子T-范畴的构造（英文）

本文首先引入了一类新的范畴A YD H G,这个范畴是一簇范畴{A YD H(α,β)}(α,β)∈G的非交并,获得了范畴{A YD H(α,β)}(α,β)∈G是一个辫子T-范畴当且仅当(A,H,Q)是一个G-偶结构,推广了2005年Panaite和Staic的主要结论.最后,当H是有限维时,构造了一个拟三角T-余代数{A#H*(α,β)}(α,β)∈G,它的表示范畴与{A YD H(α,β)}(α,β)∈G是同构的.     

L—fuzzyLocale理论与分配格的L—fuzzy拓扑表示

首先文中引入了Ｌ—ｆｕｚｚｙｌｏｃａｌｅ范畴，并证明了该范畴与满层Ｌ—ｆｕｚｚｙ拓扑空间范畴的关系类似于ｌｏｃａｌｅ与拓扑空间的联系．其次，文中建立了分配格的ｌｏｃａｌｅ式ｆｕｚｚｙＳｔｏｎｅ表示，并且与经典结果一致，任一分配格的Ｌ—ｆｕｚｚｙｌｏｃａｌｅ表示的点空间就是它的Ｌ—ｆｕｚｚｙ谱空间．     

范畴的K—根与Jacobson结构定理

本文得到三方面结果：（1）定义加法范畴的K－根，给出它的模刻划式。（2）给出J－根的内部刻划。（3）给出J－半单范畴结构中由本原范畴组成的完全同态象类的具体形式和范畴为J－半单范畴的充要条件。     

L-fuzzy集理论的范畴基础与层表示

鉴于L-fuzzy集在理论上的重要性和应用上的广泛性,旨在建立L-fuzzy集理论的范畴基础与它的层表示,提出完备范畴中对象上的格值结构概念,这一概念是L-fuzzy结构在范畴层面上的提升,进一步提出完备范畴上格值结构提升范畴概念,证明了在集合范畴中L-fuzzy结构与格值结构是同构的.以集层、群层、环层和左R-模层以及Grothendieck层等概念为基础,提出完备范畴中对象上的层结构以及完备范畴上层结构提升范畴概念,证明了在集合范畴中L-fuzzy结构与层结构也是同构的.     

半格与Domain的表示

引入一种半格———Ｄ 半格，建立了Ｄ－半格的表示理论，利用它得到了Ｌ ｄｏｍａｉｎ（即局部代数格）的表示理论；证明了Ｌ ｄｏｍａｉｎ与稳定映射范畴对偶等价于稳定Ｄ 半格与Ｄ－半格同态范畴．     

Statistical evaluation of forming limit diagram for annealed Al 1350 alloy sheets using first order reliability method

This paper investigates the formability and forming limit curve of aluminium alloy sheet of grade Al 1350 with respect to annealing temperature and strain conditions through statistical approach. The uncertainty of forming limit curve (FLC) due to anisotropy parameter and strain hardening exponent have also been taken into consideration. The plastic instability criteria and its relevant equations given by Hill have been used to construct the theoretical FLC which is compared with experimental FLC. The stochastic modeling has been made on the statistical evaluation of the FLC with a high confidence level. First Order Reliability Method (FORM) and Monte-Carlo simulation (MCS) methods have been used to compare the probability of the data points determining FLC by considering normal distribution of material properties.     

A genetic-fuzzy approach for mobile robot navigation among moving obstacles

In this paper, a genetic-fuzzy approach is developed for solving the motion planning problem of a mobile robot in the presence of moving obstacles. The application of combined soft computing techniques — neural network, fuzzy logic, genetic algorithms, tabu search and others — is becoming increasingly popular among various researchers due to their ability to handle imprecision and uncertainties that are often present in many real-world problems. In this study, genetic algorithms are used for tuning the scaling factors of the state variables (keeping the relative spacing of the membership distributions constant) and rule sets of a fuzzy logic controller (FLC) which a robot uses to navigate among moving obstacles. The use of an FLC makes the approach easier to be used in practice. Although there exist many studies involving classical methods and using FLCs they are either computationally extensive or they do not attempt to find optimal controllers. The proposed genetic-fuzzy approach optimizes the travel time of a robot off-line by simultaneously finding an optimal fuzzy rule base and optimal scaling factors of the state variables. A mobile robot cant then use this optimal FLC on-line to navigate in presence of moving obstacles. The results of this study on a number of problem scenarios show that the proposed genetic-fuzzy approach can produce efficient knowledge base of an FLC for controlling the motion of a robot among moving obstacles.     

L2-stabilization design for fuzzy control systems

System's stability is the most important requirement in control system designs. Fuzzy control system (FCS) should satisfy this requirement also. This paper shows that a linear plant with the formulated Fuzzy Logic Controller (FLC) is a nonlinear system and its stability can be analyzed by applying the Small Gain Theorem or the Circle Criterion. By these two criteria, three FLC design procedures are introduced to guarantee the stabilization of the FCS. Finally, two examples are given to confirm the availability of the proposed design approaches.     

Vibration control of active vehicle suspension system using fuzzy logic algorithm

Vehicle suspension along with tires and steering linkages is designed for safe vehicle control and to be free of irritating vibrations. Therefore the suspension system designs are a compromise between ride softness and handing ability. However, this work is concerned with a theoretical investigation into the ride behavior of actively suspended vehicles. It is based on using fuzzy logic control (FLC) to implement a new sort of active suspension system. Comparisons between the behavior of active suspension system with FLC with those obtained from active systems with linear-quadratic regulator (LQR), ideal skyhook system and the conventional passive suspension systems. Results are introduced in such a way to predict the benefits that could be achieved from a fuzzy logic system over other competing systems. Furthermore, a controller is designed and made by using results of FLC system, theoretical inputs are used to examine the validity of this controller. Moreover, comparison between actual outputs from this controller with those obtained theoretically is made to judge the validity of the controller. The results indicate that the controller has a good capability in simulation of the theoretical model.     

Stanley-Reisner ideals whose powers have finite length cohomologies

We introduce a class of Stanley-Reisner ideals called a generalized complete intersection, which is characterized by the property that all the residue class rings of powers of the ideal have FLC. We also give a combinatorial characterization of such ideals.

     

A combined genetic algorithm-fuzzy logic controller (GA–FLC) in nonlinear programming

This paper presents a combined genetic algorithm-fuzzy logic controller (GA–FLC) technique for constrained nonlinear programming problems. In the standard Genetic algorithms, the upper and lower limits of the search regions should be given by the decision maker in advance to the optimization process. In general a needlessly large search region is used in fear of missing the global optimum outside the search region. Therefore, if the search region is able to adapt toward a promising area during the optimization process, the performance of GA will be enhanced greatly. Thus in this work we tried to investigate the influence of the bounding intervals on the final result. The proposed algorithm is made of classical GA coupled with FLC. This controller monitors the variation of the decision variables during process of the algorithm and modifies the boundary intervals to restart the next round of the algorithm. These characteristics make this approach well suited for finding optimal solutions to the highly NLP problems. Compared to previous works on NLP, our method proved to be more efficient in computation time and accuracy of the final solution.     

Neuro-fuzzy technique for navigation of multiple mobile robots

In this paper, navigation techniques for several mobile robots are investigated in a totally unknown environment. In the beginning, Fuzzy logic controllers (FLC) using different membership functions are developed and used to navigate mobile robots. First a fuzzy controller has been used with four types of input members, two types of output members and three parameters each. Next two types of fuzzy controllers have been developed having same input members and output members with five parameters each. Each robot has an array of sensors for measuring the distances of obstacles around it and an image sensor for detecting the bearing of the target. It is found that the FLC having Gaussian membership function is best suitable for navigation of multiple mobile robots. Then a hybrid neuro-fuzzy technique has been designed for the same problem. The neuro-fuzzy technique being used here comprises a neural network, which is acting as a pre processor for a fuzzy controller. The neural network considered for neuro-fuzzy technique is a multi-layer perceptron, with two hidden layers. These techniques have been demonstrated in simulation mode, which depicts that the robots are able to avoid obstacles and reach the targets efficiently. Amongst the techniques developed neuro-fuzzy technique is found to be most efficient for mobile robots navigation. Experimental verifications have been done with the simulation results to prove the authenticity of the developed neuro-fuzzy technique.     

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。     

Flocking of mobile intelligent agents on fuzzy system with optimal theories

A dynamical model is presented for autonomous mobile intelligent agents. Based on the local information of the swarm, a fuzzy logical controller (FLC) is built for the attraction/repulsion function. The flocking of the separation, cohesion and alignment are achieved by combining with the rate consensus algorithm. Based on the optimal controller theories, a performance target is used to measure the states of the system. By applying the connected network from the individual local perceived information, the aggregation of the multi-agent systems can swarm following a whole consensus in the computer simulations.     

Chaos synchronization using fuzzy logic controller

The design of a rule-based controller for a class of master-slave chaos synchronization is presented in this paper. In traditional fuzzy logic control (FLC) design, it takes a long time to obtain the membership functions and rule base by trial-and-error tuning. To cope with this problem, we directly construct the fuzzy rules subject to a common Lyapunov function such that the master–slave chaos systems satisfy stability in the Lyapunov sense. Unlike conventional approaches, the resulting control law has less maximum magnitude of the instantaneous control command and it can reduce the actuator saturation phenomenon in real physic system. Two examples of Duffing–Holmes system and Lorenz system are presented to illustrate the effectiveness of the proposed controller.