模糊系统H∞控制器设计的LMI方法

应用LMI(线性矩阵不等式)方法,研究了T-S模糊系统H_∞控制器的设计问题.首先给出了T-S模糊系统基于状态反馈H_∞控制存在的两个新的充分条件.新条件不但简洁而且把模糊子系统间的相互作用表示为由子系统的系数矩阵构成的矩阵不等式.然后新条件被转化为可直接应用Matlab求解的线性矩阵不等式.最后应用线性矩阵不等式方法和Matlab,给出了T-S模糊系统H_∞控制器的设计方法.     

基于聚类有效性分析的模糊粗糙集归纳学习方法

引入模糊C均值聚类算法进行连续属性模糊化,通过聚类有效性分析来确定最佳分类数目,克服了属性模糊化方法需要人为确定划分类数的缺点。用属性模糊化得到的属性隶属度矩阵约简模糊粗糙属性,由此提出一种基于模糊粗糙集的属性约简算法。实例验证了该方法的可行性和有效性。     

标签分布熵正则的模糊C均值平衡聚类方法

许多应用场景要求每个类别的数量相对平衡,而传统模糊C均值(FCM)聚类算法无法实现此功能.为此,利用标签信息构造标签分布熵评价聚类的平衡度,然后将标签分布熵、模糊隶属度矩阵与标签矩阵之间的平方损失同时引入到传统FCM中,进而提出一种标签分布熵正则的模糊C均值平衡聚类方法 (FCMLDE).同时,利用迭代方法和增广拉格朗日乘数法设计该模型的优化算法.最后,利用6个真实数据集进行聚类实验,结果表明,所提方法在聚类性能和平衡性能上均具有很好的优势.     

二汽车身厂MIS规划逻辑结构设计

本文运用BSP的理论和方法及Authony的三阶段管理理论，对过程和数据类的关系进行了分析、合并;按企 业生产管理的三个层次(决策控制层、管理、操作)及车身厂的本身特点，将识别出的过程划分为十功能组;分别作出7 十个功能组的过程与数据类关系U/C矩阵表和系统的U/C矩阵表。     

基于直觉模糊包含度的聚类有效性分析

针对直觉模糊集合数据的聚类有效性问题,提出了一种基于直觉模糊包含度的聚类有效性分析方法。该方法采用直觉模糊包含度和直觉模糊划分熵来评价直觉模糊聚类的有效性。其中,直觉模糊包含度通过增加非隶属度参数对模糊包含度进行直觉化扩展,用于评价类与类间包含的程度;而直觉模糊划分熵用于检验分类结果的可靠性。最后通过典型实例验证了该方法的有效性。     

基于模式运动的一类生产过程调节性能与聚类参数关系

为研究基于模式运动的系统动力学描述方法中聚类参数对生产过程调节性能的影响,给出描述系统动态调节性能与产品质量调节性能的指标,分析并建立了聚类参数与系统调节性能间的关系;介绍了基于模式运动的一类复杂生产过程建模方法,并利用LMI方法给出了状态反馈控制器设计方法;提出了基于粒子群优化方法的最大熵聚类算法,定义并提取了系统调节性能指标;利用提出的新的覆盖分类神经网络,建立最大熵聚类方法的参数与调节性能间的映射关系,并分析了分类网络泛化能力;采用实际烧结矿生产数据进行仿真,结果表明所提方法可以分析与建立调节性能与聚类参数间的关系,且可为实际生产中聚类参数的选择提供一定的依据.     

模糊聚类算法的研究与实现

聚类就是按照事物间的相似性进行区分和分类的过程,传统的聚类分析是一种硬划分,它把每个待辨识的对象严格地划分到某个类中,具有非此即彼的性质,因此这种分类的类别界限是分明的。而实际上大多数对象并没有严格的属性,它们在形态和类属方面存在着中介性,适合进行软划分。1965年,模糊理论的创始人Zadeh提出的模糊集理论为这种软划分提供了有力的分析工具,人们开始用模糊的方法来处理聚类问题,并称之为模糊聚类。该文主要内容是研究和实现基于等价关系的模糊聚类算法,该算法以隶属度作为聚类的出发点,以模糊等价矩阵作为启发规则。首先根据给出的样本,通过数据标准化求得数据矩阵;其次根据数量积法对数据矩阵进行标定即建立模糊相似矩阵;再次通过传递闭包法把模糊相似矩阵转换成模糊等价矩阵,在模糊等价矩阵中取不同的元素作为阈值λ,再根据λ截矩阵的定义把模糊等价矩阵转换成只有0和1的矩阵;最后,把该矩阵中元素相同的列聚为同一类。通过实例分析运用基于等价关系的模糊聚类算法进行聚类结果是正确的。     

DNA序列分析系统的开发应用

20世纪90年代,人类基因组计划的启动,有力推动了DNA测序工作的发展。寻找某些特征片段(功能片段)在序列中的分布规律,对遗传学、生物信息学等都有重要的应用意义。在教学、研究中发现,应用数学分析软件MATLAB的字符串处理功能,可以容易地达到功能片段分析的目的,本系统通过分析DNA序列链之间的关联程度,构造出特征矩阵,根据模糊C均值算法较准确的对DNA序列的集合进行了分类,同时利用matlab的图像显示功能将聚类的最终结果清楚明了的显示在图像中,使用户能清楚的看到聚类效果。本系统主要研究了DNA链碱基序列分析、多个DNA链特征矩阵提取、模糊C均值聚类算法分类DNA等三大部分。首先该系统对DNA序列的总长度和功能序列的长度进行了测量,利用一维数组确定功能片段在DNA序列中的位置特征,从而完成了对DNA碱基序列的分析;其次该系统对用户给出的数个DNA链进行序列之间的特征分析,统计出每个序列的(A,T,C,G)碱基密度,得到一个特征矩阵,有效的为模糊聚类分析方法提供数据来源。最终该系统应用模糊C均值聚类算法,利用特征矩阵的数值,将数个DNA序列聚类并分为两类。     

DNA序列分析系统的开发应用

20世纪90年代,人类基因组计划的启动,有力推动了DNA测序工作的发展。寻找某些特征片段（功能片段）在序列中的分布规律,对遗传学、生物信息学等都有重要的应用意义。在教学、研究中发现,应用数学分析软件MATLAB的字符串处理功能,可以容易地达到功能片段分析的目的,本系统通过分析DNA序列链之间的关联程度,构造出特征矩阵,根据模糊C均值算法较准确的对DNA序列的集合进行了分类,同时利用matlab的图像显示功能将聚类的最终结果清楚明了的显示在图像中,使用户能清楚的看到聚类效果。本系统主要研究了DNA链碱基序列分析、多个DNA链特征矩阵提取、模糊C均值聚类算法分类DNA等三大部分。首先该系统对DNA序列的总长度和功能序列的长度进行了测量,利用一维数组确定功能片段在DNA序列中的位置特征,从而完成了对DNA碱基序列的分析;其次该系统对用户给出的数个DNA链进行序列之间的特征分析,统计出每个序列的（A,T,C,G）碱基密度,得到一个特征矩阵,有效的为模糊聚类分析方法提供数据来源。最终该系统应用模糊C均值聚类算法,利用特征矩阵的数值,将数个DNA序列聚类并分为两类。     

模糊判断矩阵环境下的大型群决策方法

为解决大型的群决策问题,对传统的模糊C均值算法(FCM)进行了扩展。通过扩展的算法对专家个体模糊判断矩阵聚类,获取模糊划分矩阵和聚类原型,根据模糊划分矩阵确定类权重,进而利用WAA算子对聚类原型进行集结,求取群综合模糊判断矩阵。通过算例验证了该算法的可行性。     

Reflections on the computer in management of production systems

The production system is an economic system managed by man and composed of man. The subsystems of the production system can be divided into reactive responsive and purposeful ones. On the basis of a multitude of components constituting purposeful systems (people) the productions systems as economic systems can be divided into elementary, simple and complex ones. The computer is an artificial system, capable of data storing and processing, or respectively capable of directly causing changes in states of other systems. One can distinguish two computer functions, namely an information function which consists of the intellectual preparation of human actions, and an interference function consisting of the technical causing of changes in states of other systems. So in speaking of the computer-aided management of production systems one implies such a human interference in the behaviour of production systems and their subsystems which is made by the aid of the computer. This interference may refer to reactive and responsive systems (subsystems) as well as to purposeful systems, i.e. people. It implies various applications of the computer in both functions.     

基于脆性联系熵的复杂系统崩溃致因研究

针对开放的复杂系统进行研究，首次提出并论证了脆性是复杂系统的一个基本特性。根据集对分析的理论，定义了子系统间的脆性联系熵、脆性基元的概念，同时将非合作博弈的理论和方法引入到复杂系统的脆性的研究中。基于复杂系统博弈的动力学，建立复杂系统脆性仿真模型，仿真结果说明复杂系统的崩溃，是由于基元内子系统的熵值在外界干扰过程中不断增加，而且又无法从周围环境得到负熵流的补充时，达到临界熵值而导致崩溃，     

Mathematical methods for the modular design of computer systems

An approach to modular design is proposed, involving the estimation of the information transfer between the modules of acomplex system.In apreviouspaper[l], a general decomposition criterion was derived, employing the entropy function as a measure of the amount of information contained within a system or subsystems. This paper concerns the formulation of an algorithm for the optimisation of the criterion which decomposes hierarchically a system into its most independent subsystems or modules. A simple illustrative example is given and further, the design methodology is applied to detect the modular structure of a computer teaching system.     

Entropy metrics for software design evaluation

Several metrics for the quality assessment of a software system design are discussed. The metrics are based on the entropy function of communication information theory. The design of software systems is viewed as a trade-off between the information contained within a subsystem and the information shared among the subsystems of a given system. Since information can be shared in different ways by different system designs, we can compute the excess entropy and thereby rank different design alternatives. Consequently, the quality improvement due to reconfigurations can be determined by calculating the excess entropies for each reconfiguration.     

Asymptotic stability and instability of large-scale systems

The purpose of this paper is to develop new methods for constructing vector Lyapunov functions and broaden the application of Lyapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. By redefining interconnection functions among the subsystems according to interconnection matrices, the same mathematical machinery can be used to determine connective asymptotic stability of large-scale systems under arbitrary structural perturbations. With minor technical adjustments, the theory is broadened to include considerations of unstable subsystems as well as instability of composite systems.     

复杂系统可靠性多级综合的熵法第二近似限

根据信息量相等的原理，将部件或分系统的试验信息折合为产品的等效试验信息，导出指出寿命型系统的部件或分系统试验信息等效折合的基本公式，根据单元可靠性评定的基本理论，给出院 基于信息理论的复杂系统可靠性第二近似限的基本模型。计算实例说明了模型的具体应用，并与传统方法的评定结果进行比较，说明了模型的正确性和实用性。     

Vector dissipativity theory and stability of feedback interconnections for large-scale non-linear dynamical systems

Recent technological demands have required the analysis and control design of increasingly complex, large-scale non-linear dynamical systems. In analysing these large-scale systems, it is often desirable to treat the overall system as a collection of interconnected subsystems. Solution properties of the large-scale system are then deduced from the solution properties of the individual subsystems and the nature of the system interconnections. In this paper we develop an analysis framework for large-scale dynamical systems based on vector dissipativity notions. Specifically, using vector storage functions and vector supply rates, dissipativity properties of the composite large-scale system are shown to be determined from the dissipativity properties of the subsystems and their interconnections. Furthermore, extended Kalman–Yakubovich–Popov conditions, in terms of the subsystem dynamics and interconnection constraints, characterizing vector dissipativeness via vector system storage functions are derived. Finally, these results are used to develop feedback interconnection stability results for large-scale non-linear dynamical systems using vector Lyapunov functions.     

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H₂ performance and the H_∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H₂/H_∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H₂/H_∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H_∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.     

Dissipativity reinforcement in feedback systems and its application to expanding power systems

This paper focuses on the performance analysis and improvement of interconnected passive systems. We assume that each subsystem has a special passivity property that is characterized by 2 parameters. The parameters are also utilized for evaluating the dissipation performance as the L₂‐gain. Then, the feedback system composed of passive subsystems inherits the parameter‐dependent passivity, and the parameter transition is given. In addition, it is shown that the dissipation performance of the feedback system is strictly improved as compared with that of the subsystems, which is called dissipativity reinforcement in this paper. Furthermore, we expand the feedback system to a larger‐scale system via the iterative feedback connection of the passive subsystems. Then, the performance of the entire system is gradually reinforced with the increase in the number of subsystems. Subsequently, we extend the class of parameter‐dependent passivity to a frequency‐dependent one. Finally, dissipativity reinforcement via an iterative feedback connection is applied to a power system that involves a large number of renewable energy generators. In particular, we propose a strategy for designing the power system, such that the dissipation performance of the entire system is gradually reinforced via scale expansion, ie, with the increase in the amount of energy generators installed.     

Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems

An adaptive fuzzy control approach is proposed for a class of multiple-input-multiple-output (MIMO) nonlinear systems with completely unknown nonaffine functions. The MIMO systems are composed of n subsystems and each of subsystems is in the nested lower triangular form. It is difficult and complicated to control this class of systems due to the existence of unknown nonaffine functions and the couplings among the nested subsystems. This difficulty is overcome by introducing some special type Lyapunov functions and taking advantage of the mean-value theorem, the backstepping design method and the approximation property of the fuzzy systems. The proposed control approach can guarantee that all the signals in the closed-loop system are bounded. A simulation experiment is utilized to verify the feasibility of the proposed approach.