A systematic approach to improve multiple Lyapunov function stability and stabilization conditions for fuzzy systems

This paper presents a systematic approach for decreasing conservativeness in stability analysis and control design for Takagi-Sugeno (TS) systems. This approach is based on the idea of multiple Lyapunov functions together with simple techniques for introducing slack matrices. Unlike some previous approaches based on multiple Lyapunov functions, both the stability and the stabilization conditions are written as linear matrix inequality (LMI) problems. The proposed approach reduces the number of inequalities and guarantees extra degrees of freedom to the LMI problems. Numeric examples illustrate the effectiveness of this method.     

Embedding a fault-free hamiltonian cycle in a class of faulty generalized honeycomb tori

Generalized honeycomb torus (GHT) is recognized as an attractive alternative to existing torus interconnection networks in parallel computing systems. Assume that m and d are integers with m ? 2 and d ? 8. This paper addresses the fault-tolerant hamiltonicity of GHT(m, 2d, d) with fault set F = {(w, y), (x, y)}, where w < x, w + y is even and x + y is odd. We show that such a faulty GHT is hamiltonian by presenting a systematic method for constructing a fault-free hamiltonian cycle. This result reveals another appealing feature of GHTs.     

Predictive models for emission of hydrogen powered car using various artificial intelligent tools

This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors are developed by means of application of various Artificial Intelligent (AI) models namely; AI software built at the University of Tasmania, back-propagation neural networks with Levenberg–Marquardt algorithm, and adaptive neuro-fuzzy inference systems. These predictions are based on the study of qualitative and quantitative effects of engine process parameters such as mass airflow, engine speed, air-to-fuel ratio, exhaust gas temperature and engine power on the harmful exhaust gas emissions. All AI models show good predictive capability in estimating the emissions. However, excellent accuracy is achieved when using back-propagation neural networks with Levenberg–Marquardt algorithm in estimating emissions for various hydrogen engine operating conditions with the predicted values less than 6% of percentage average root mean square error.     

A hybrid multi-criteria decision-making model for firms competence evaluation

In this paper, we present a hybrid multi-criteria decision-making (MCDM) model to evaluate the competence of the firms. According to the competence-based theory reveals that firm competencies are recognized from exclusive and unique capabilities that each firm enjoy in marketplace and are tightly intertwined within different business functions throughout the company. Therefore, competence in the firm is a composite of various attributes. Among them many intangible and tangible attributes are difficult to measure. In order to overcome the issue, we invite fuzzy set theory into the measurement of performance. In this paper first we calculate the weight of each criterion through adaptive analytic hierarchy process (AHP) approach (A³) method, and then we appraise the performance of firms via linguistic variables which are expressed as trapezoidal fuzzy numbers. In the next step we transform these fuzzy numbers into interval data by means of α-cut. Then considering different values for α we rank the firms through TOPSIS method with interval data. Since there are different ranks for different α values, we apply linear assignment method to obtain final rank for alternatives.     

一种含噪数据FCM聚类算法

针对IADFCM算法在运算过程中忽略区间中点和半宽对区间数分析的问题,给出基于中点、半宽含权重区间数间的欧氏距离,提出一种改进的聚类分析算法,对模拟数据集和实际数据集分别进行仿真实验,实验结果表明,该算法是有效的。     

基于使用控制模型的防恶意下载系统

为了对恶意下载行为实施有效控制,研究通用访问控制框架和使用控制模型(UCON),提出基于流量的UCON。设计并实现基于UCON的防恶意下载系统,阐述其关键技术和实现方法。实验结果表明,该模型能有效控制用户下载行为,具有高安全性和较强的操作灵活性。     

四自由度并联跟踪台的软件关键技术

研究四自由度并联跟踪台中的软件关键技术,编写Matlab仿真程序对并联跟踪台进行参数化设计,利用Solidworks与ADAMS联合仿真软件获取并联跟踪台的运动学和动力学性能参数,通过对操纵杆的编程实现对并联跟踪台的手动控制。实验结果表明,四自由度并联跟踪台设计合理、运动灵活、手控效果好。     

基于模糊支持向量机的步态识别

提出基于模糊支持向量机（FSVM）的步态识别方法,以人体步态的宽度向量作为特征,探讨直接取值法和模糊C均值2种模糊隶属度确定方法对FSVM步态分类效果的影响。实验结果表明,模糊C均值法的识别率均略好于SVM,直接取值法的识别率甚至低于SVM,因此,选取正确的模糊隶属度确定方法是FSVM能否成功应用于步态识别的关键。     

冷床区钢坯自动跟踪系统关键技术的研发

安钢中板厂的炉号跟踪系统中,冷金属检测器CMD用来检测冷床区钢坯的运动,但是CMD只能检测出辊道上是否有钢坯经过,而不能判断钢坯在冷床区具体上到哪个冷床,因此,目前冷床部分的钢坯跟踪是靠人工手动完成的.针对该问题,提出一种新的运用数字图像处理技术完成冷床区钢坯自动跟踪的方法.该方法利用运动目标检测方法检测出辊道上有钢坯运动,然后经过最佳阈值分割、改进的区域生长算法、质心标记、数据库程序等步骤完成钢坯运动轨迹的标记,实现自动跟踪.     

Necessary optimality conditions for fuzzy variational problems

The main aims of this study are to derive the fuzzy Euler-Lagrange conditions for both fuzzy unconstrained and constrained variational problems based on the concepts of differentiability and integrability of a fuzzy mapping that may be parameterized by the left and right-hand functions of its α-level sets.