A study of fuzzy logical petri nets and its application

In this paper, a fuzzy Petri net approach to modelling fuzzy rule-based reasoning is proposed. Logical Petri net (LPN) and fuzzy logical Petri net (FLPN) are defined. The backward reasoning algorithm based on sub-fuzzy logical Petri net is given. It is simpler than the conventional algorithm of forward reasoning; from initial propositions. An application to the partial fault model of a car engine in paper Portinale's(1993) is used as an illustrative example of FLPN.     

一种基于模糊理论的图像边缘提取

讨论了模糊理论在边缘提取中的应用，并给出了一种改进的基于模糊理论的图像边缘检测算法。实验结果表明，与该算法不需要加额外的滤波器或图像降噪预处理。在抗噪性能方面(80％以内的Gaussian噪声和10％以内的椒盐噪声Salt＆Pepper)明显优于其它方法。     

Knowledge-based fuzzy color processing

This paper concerns the application of digital image processing in combination with rulebased reasoning as a nondestructive quality testing method for resistance spot welding. The use of fuzzy logic gives the possibility to characterize colors by linguistic terms rather than by names for wavelength or wavelength intervals. The presented method supplements Lotfi Zadeh's idea of soft computing and computing with words. It can be applied to many problems in which color carries important information.     

A novel temporal error concealment method based on fuzzy reasoning for H.264

In this paper, a fuzzy reasoning based temporal error concealment method is proposed. The basic temporal error concealment is implemented by estimating Motion Vector (MV) of the lost MacroBlock (MB) from its neighboring MVs. Which MV is the most proper one is evaluated by some criteria. Generally, two criteria are widely used, namely Side Match Distortion (SMD) and Sum of Absolute Difference (SAD) of corresponding MV. However, each criterion could only partly describe the status of lost block. To accomplish the judgement more accurately, the two measures are considered together. Thus a refined measure based on fuzzy reasoning is adopted to balance the effects of SMD and SAD. Terms SMD and SAD are regarded as fuzzy input and the term ‘similarity’ as output to complete fuzzy reasoning. Result of fuzzy reasoning repre-sents how the tested MV is similar to the original one. And k-means clustering technique is performed to de-fine the membership function of input fuzzy sets adaptively. According to the experimental results, the con-cealment based on new measure achieves better performance.     

自适应模糊滑模控制器设计

针对传统滑模控制的抖振问题,利用线性化反馈技术,将模糊自适应和滑模控制相结合,设计一种新型的模糊滑模控制器。通过模糊推理和基于Lyapunov函数的稳定性分析,获得模糊控制规则的自适应律,构成自适应模糊滑模控制器,有效解决了传统滑模控制中,需要确定参数摄动和外部干扰上确界不确定性问题,倒立摆上的运行结果表明该方法的有效性。     

模糊自适应估计器在INS/GPS组合导航中的应用研究

研究了一种模糊自适应神经网络状态估计器的工作原理及结构,并讨论了用其代替传统扩展卡尔曼滤波在导航参数估计中的实现方法。利用扩展卡尔曼滤波来构造模糊推理系统,通过神经网络对模糊推理系统进行训练,根据输入输出样本自动调整模糊系统的设计参数,从而实现对INS/GPS组合导航系统导航参数的最优估计。通过仿真验证表明,用模糊自适应状态估计方法进行导航系统的初始对准,能够大大提高系统的实时性。     

基于单片机模糊推理的洗衣机控制系统设计

为了更好的模仿人工洗涤过程,提高洗衣机的洗涤质量,针对以单片机为核心的洗衣机控制系统,引入了模糊推理技术。首先阐述了模糊洗衣机的基本原理,完成了系统硬件设计;在软件方面,对检测到的水温及肮脏度、衣质、衣量等物理量进行模糊化处理,建立了洗涤规则库,通过模糊推理,实现对洗涤时间、水流强弱、洗涤剂用量以及脱水时间的自动控制,提高了洗衣机的自动控制和智能化程度。     

模糊算子在图像后处理中的应用

基于规则的模糊算子可以将近似原理应用到图像处理领域内,是一种新颖的图像处理方法。针对图像压缩所带来的模糊效应,利用模糊算子在对解码后的图像进行了细节增强,部分补偿了压缩图像的损伤。     

基于模糊Petri网的网络风险评估模型

针对网络安全风险评估过程中存在的复杂性,以资产、脆弱性和威胁为安全评估的关键因素,建立安全分析的层次化评估指标体系。引入可信度概念,提出了一种基于模糊Petri网的安全风险评估模型以及模糊推理算法,同时结合层次分析法,采取定性与定量分析相结合的方法进行安全评估。实例分析表明：与传统的综合风险评估方法相比,基于模糊Petri网的风险评估方法给出的结果更加准确和科学。因此,该方法更适合应用于实际的网络系统风险评估中。     

Applications of fuzzy sets and approximate reasoning

This paper discusses recent applications of fuzzy sets and the theory of approximate reasoning. The primary focus is on fuzzy logic control (FLC). We begin with a brief history of the key ideas, a survey of recent applications, and a discussion of the genesis of FLC in Japan. We then turn to a study of the general principles of FLC, considering it as a combination of ideas from conventional control theory, artificial intelligence, and fuzzy sets theory. We next provide a detailed analysis of a simple application in consumer electronics, namely, a fuzzy washing machine developed by Hitachi Corporation. In concluding sections we briefly consider other types of applications, including recent work on pilotless helicopters, fuzzy expert systems, and the concept of a fuzzy computer, and we discuss the potential for future developments. It is our opinion that the subject of FLC is still very much in its infancy, and that recent events mark the beginning of an entirely new genre of “intelligent” control     

遗传算法优化模糊控制器参数的方法研究

基于遗传算法对模糊控制器参数进行寻优,首先采用模糊规则,通过模糊推理的方法对二阶系统进行仿真实验,仿真结果表明系统动态响应超调小、调节时间短,具有良好的性能;然后采用遗传算法,按照ITAE准则对控制器的参数进行优化,仿真结果表明动态性能比模糊控制显著改善,显示出遗传算法对模糊控制器参数寻优的有效性和优越性。     

基于模糊神经网络的目标识别

结合模糊推理和神经网络两种方法的优点,从网络的结构、工作过程、学习算法等方面,探讨了一种基于模糊神经网络(FNN)的目标识别方法。通过仿真结果证明,此方法确实可行。     

A fuzzy operator for the enhancement of blurred and noisy images

Rule-based fuzzy operators are a novel class of operators specifically designed in order to apply the principles of approximate reasoning to digital image processing. This paper shows how a fuzzy operator that is able to perform detail sharpening but is insensitive to noise can be designed. The results obtainable by the proposed technique in the enhancement of a real image are presented.     

Stochastic stability analysis of fuzzy hopfield neural networks with time-varying delays

The ordinary Takagi-Sugeno (TS) fuzzy models have provided an approach to represent complex nonlinear systems to a set of linear sub-models by using fuzzy sets and fuzzy reasoning. In this paper, stochastic fuzzy Hopfield neural networks with time-varying delays (SFVDHNNs) are studied. The model of SFVDHNN is first established as a modified TS fuzzy model in which the consequent parts are composed of a set of stochastic Hopfield neural networks with time-varying delays. Secondly, the global exponential stability in the mean square for SFVDHNN is studied by using the Lyapunov-Krasovskii approach. Stability criterion is derived in terms of linear matrix inequalities (LMIs), which can be effectively solved by some standard numerical packages.     

模糊推理合成法在弹道处理中的应用

采用模糊推理合成法处理弹道问题，是弹道处理中的又一种新方法。本文通过对某空地导弹发射包线中的最大允许发射距离的实例计算，证明了应用模糊推理合成法处理弹道问题的正确性与可行性。     

多传感器模糊D-S理论辐射源识别

研究了将D-S证据理论与模糊推理组合应用辐射源识别的方法,提出了基于模糊综合评估获取基本概率分配函数的方法;在此基础上研究了应用D-S证据理论进行多传感器信息融合,从而识别雷达辐射源的原理;仿真实验和对比实验表明本算法的有效性。     

基于模糊控制的电动汽车再生制动系统的研究

再生制动能够降低能源的消耗量和延长电动汽车的行驶里程。它广泛的受到诸多学者的关注。本文提出了一个新颖的再生制动控制系统。该系统基于无刷直流电机的控制特性和电动汽车刹车时的制动特性,直流无刷电机采用传统的PID控制,刹车力采用模糊逻辑控制,刹车力矩可以由PID控制器实时的控制。通过Matlab/Simulink软件,仿真分析了电池的充电状态、制动力和直流侧线电流。实验和仿真结果均证实了在具有良好的刹车性能的前提下,该方法可以实现良好的再生制动性能和延长电动汽车的行驶里程,在工程上更加易于实现也具有更好的鲁棒性和更高的效率。     

Two-stage fuzzy inference system for symbolic simplification of analog circuits

This paper presents a knowledge-based fuzzy approach to symbolic circuit simplification in an effort to imitate human reasoning and knowledge of circuit designer experts. The fuzzy approach differs from the conventional simplification techniques in that it can efficiently combine different input variables to obtain optimal simplified expressions. Additionally, this method was chosen due to its adjustability and interpretability, as well as its ability to manage very complex symbolic expressions. The proposed algorithm uses fuzzy logic to simplify the symbolic circuit transfer functions in two stages. In the first stage, a fuzzy system is applied to directly eliminate nonessential circuit components, resulting simplified circuit topology which also yields simpler transfer function. In the second stage, another fuzzy system is used to further simplify the symbolic transfer function from the already simplified circuit, such that deeper insight into the circuit behavior can be obtained. Symbolic and numerical results show that the fuzzy approach outperforms the conventional techniques in terms of accuracy, expression complexity, and CPU running time.