Improved fuzzy identification method based on Hough transformation and fuzzy clustering

This paper presents an approach that is useful for the identification of a fuzzy model in SISO system. The initial values of cluster centers are identified by the Hough transformation, which considers the linearity and continuity of given input-output data, respectively. For the premise parts parameters identification, we use fuzzy-C-means clustering method. The consequent parameters are identified based on recursive least square. This method not only makes approximation more accurate, but also let computation be simpler and the procedure is realized more easily. Finally, it is shown that this method is useful for the identification of a fuzzy model by simulation.     

A NEW APPROACH ON IDENTIFICATION OF BOUNDARY PARAMETER FOR A TWODIMENSIONAL DIFFUSION SYSTEM

This paper presents a new approach of the boundary parameter identification of adiffusion system.The system model is governed by a two-dimensional parabolic problem,which involves an unknown boundary parameter.Identifiability of the boundary parameterand the new approach are discussed briefly,which show that the new approach can overcomenot only the ill-posedness of the nonlinear output least square method but also the difficultyof numerical computation of the nonlinear output least square estimate due to the existenceof the local minima of the performance functional,Finally,some numerical examples aregiven.     

Disturbance Attenuation State-Feedback Control for Uncertain Interconnected Systems

This paper studies the problem of robust H∞ control design for a class of uncertain interconnected systems via state feedback. This class of systems are described by a state space model, which contains unknown nonlinear interaction and time-varying norm-bounded parametric uncertainties in state equation. Using the Riccati-equation-based approach we design state feedback control laws, which guarantee the decentralized stability with disturbance attenuation for the interconnected uncertain systems. A simple example of an interconnected uncertain linear system is presented to illustrate the results.     

Best weight pattern evaluation based security constrained power dispatch algorithm

This paper presents a methodology which determines the allocation of power demand among the committed generating units while minimizes number of objectives as well as meets physical and technological system constraints. The procedure considers two decoupled problems based upon the dependency of their goals on either active power or reactive power generation. Both the problems have been solved sequentially to achieve optimal allocation of active and reactive power generation while minimizes operating cost, gaseous pollutants emission objectives and active power transmission loss with consideration of system operating constraints along with generators prohibited operating zones and transmission line flow limits. The active and reactive power line flows are obtained with the help of generalized generation shift distribution factors （GGDF） and generalized Z-bus distribution factors （GZBDF）, respectively. First problem is solved in multi-objective framework in which the best weights assigned to objectives are determined while employing weighting method and in second problem, active power loss of the system is minimized subject to system constraints. The validity of the proposed method is demonstrated on 30-bus IEEE power system.     

Online Delay-Evaluation Approach in Networked Control Systems

This paper presents an online evaluation approach of time delays for networked control systems (NCS), which characterizes the time delays without any synchronized clock in the network and any assumptions of time delays. With this approach, an optimal control scheme based on the approach is designed to achieve the desired performance despite the uncertain delays in the system. The experimental results based on CANbus illustrate the effectiveness of the proposed control design and satisfactory performance of the closed-loop system.     

Using Multi-input-layer Wavelet Neural Network to Model Product Quality of Continuous Casting Furnace and Hot Rolling Mill

A new architecture of wavelet neural network with multi-input-layer is proposed and implemented for modeling a class of large-scale industrial processes. Because the processes are very complicated and the number of technological parameters, which determine the final product quality, is quite large, and these parameters do not make actions at the same time but work in different procedures, the conventional feed-forward neural networks cannot model this set of problems efficiently. The network presented in this paper has several input-layers according to the sequence of work procedure in large-scale industrial production processes. The performance of such networks is analyzed and the network is applied to model the steel plate quality of continuous casting furnace and hot rolling mill. Simulation results indicate that the developed methodology is competent and has well prospects to this set of problems.     

A Structured Methodology for Local Network Design Engineering

This paper presents a structured methodology for local network design engineering (SMLNDE). A complex and fuzzy project for local network design can be decomposed into a set of simple and particular activities using the SMLNDE. The SMLNDE allows rigorous requirements definition and permits the exhaustive consideration of the large number of factors influencing local network design engineering. The complete and clear design documentations and an optimal design can also be provided by the methodology. The SMLNDE has been implemented using the structured analysis and design technique. The study shows that the SMLNDE is an effective design methodology for the large and complex local networks.     

Adaptive augmentation of gain-scheduled controller for aerospace vehicles

This paper proposes an adaptive augmentation control design approach of the gain-scheduled controller.This extension is motivated by the need for augmentation of the baseline gainscheduled controller.The proposed approach can be utilized to design flight control systems for advanced aerospace vehicles with a large parameter variation.The flight dynamics within the flight envelope is described by a switched nonlinear system,which is essentially a switched polytopic system with uncertainties.The flight control system consists of a baseline gain-scheduled controller and a model reference adaptive augmentation controller,while the latter can recover the nominal performance of the gainscheduled controlled system under large uncertainties.By the multiple Lyapunov functions method,it is proved that the switched nonlinear system is uniformly ultimately bounded.To validate the effectiveness of the proposed approach,this approach is applied to a generic hypersonic vehicle,and the simulation results show that the system output tracks the command signal well even when large uncertainties exist.     

Approximating the Spectral Abscissa for Switched Linear Systems via Coordinate Transformations

In this paper,an approach of square coordinate transformation is proposed to approximate the spectral abscissa for continuous-time switched linear systems.By applying elementary transformations iteratively,a series of minimums of least μ1 matrix set measures are obtained,which are utilized to approximate the spectral abscissa of the switched system.The approach is developed into tractable numerical algorithms that provide upper bound estimates of the spectral abscissa.Numerical simulations show the effectiveness of the proposed method.     

A characteristic set method for solving boolean equations and applications in cryptanalysis of stream ciphers*

This paper presents a characteristic more efficient and has better properties than the set method for solving Boolean equations, which is general characteristic set method. In particular, the authors give a disjoint and monic zero decomposition algorithm for the zero set of a Boolean equation system and an explicit formula for the number of solutions of a Boolean equation system. The authors also prove that a characteristic set can be computed with a polynomial number of multiplications of Boolean polynomials in terms of the number of variables. As experiments, the proposed method is used to solve equations from cryptanalysis of a class of stream ciphers based on nonlinear filter generators. Extensive experiments show that the method is quite effective.     

专用实时操作系统的母系统及汉化

本文在分析了现有专用实时操作系统存在的问题之后,运用程序族理论和结构化程序设计方法,提出了母系统-子系统的体系结构和工作模式,并介绍了汉化母系统的设计与实现。     

智能化人口-经济发展战略决策支持系统CDSS

本文提出将基于人工智能技术、运用知识和推理的专家系统与基于数字仿真技术、运用数据和模型的仿真模型体系相集成的智能化决策支持系统CDSS。CDSS用领域专家的知识选择和组合模型,完成问题的推理和系统的仿真运行。系统支持决策过程的各阶段并通过人-机界面实现定性与定量相结合的交互式决策。其系统结构对解决管理科学中非结构化问题具有普遍适用的价值。     

利用模糊神经网络进行数据挖掘的一种算法

研究把模糊神经网络结合进数据挖掘的方法,经过模糊神经网络的建立,训练达到精度要求、网络的裁剪、隐节点激活值的聚类和规划提高的步骤,达到通过模糊神经网络方法从数据库中提取知识的目的,并通过仿真验证了算法有效性。     

一个证券组合投资分析的对策论方法

将给出证券组合投资分析的一个对策论方法 .将最小的可能收益作为风险的度量 ,将投资者的投资心理及证券市场的随机性考虑到模型之中 ,建立了证券组合投资的双层规划模型 ;对模型进行了理论分析、提出了求解算法 ;通过一个例子来说明如何用本文方法来进行证券组合投资分析.     

<Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> control for nonlinear stochastic Markov systems with time-delay and multiplicative noise

This paper is concerned with the H_∞ control problem for a class of nonlinear stochastic Markov jump systems with time-delay and system state-, control input- and external disturbancedependent noise. Firstly, by solving a set of Hamilton-Jacobi inequalities (HJIs), the exponential mean square H_∞ controller design of delayed nonlinear stochastic Markov systems is presented. Secondly, by using fuzzy T-S model approach, the H_∞ controller can be designed via solving a set of linear matrix inequalities (LMIs) instead of HJIs. Finally, two numerical examples are provided to show the effectiveness of the proposed design methods.     

基于活动的工作流建模及其动态调度研究

首先用扩展有向图的方法构造一种基于活动的工作流建模方法 .在此模型的基础上 ,通过对完成活动所需的资源、角色、时间、成本的分析 ,用人工智能的思想和方法对所建立的工作流模型进行基于规则的启发式动态调度 ,从而实现对工作流模型的动态仿真 .所提出的模型和算法紧密集成 ,易于实现 .并用一个实例对所提出的建模方法和调度过程进行了说明 .     

Robust dissipative control for time-delay stochastic jump systems

A robust dissipative control problem for a class of It?-type stochastic systems is discussed with Markovian jumping parameters and time-varying delay. A memoryless state feedback dissipative controller is developed based on Lyapunov-Krasovskii functional approach such that the closed-loop system is robustly stochastically stable and weakly delay-dependent (RSSWDD) and strictly (Q, S, R)-dissipative. The sufficient condition on the existence of state feedback dissipative controller is presented by linear matrix inequality (LMI). And the desired controller can be concluded as solving a set of LMI. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach.     

基于Rough集的空间属性数据挖掘的研究与实践

介绍了地理信息系统（GIS）的概念，深入研究了空间数据库的特性，探讨了Rough集理论，分析了Rough集合和空间数据的关系，讨论了差别矩阵的概念和算法，应用信息熵和模糊数学模型，给出了空间数据库属性数据的数据约减和数据挖掘算法，最后分析了一个应用事例，从而验证了算法的可行性。     

基于时频分析与神经网络的实时智能故障诊断系统的软件设计--数据格式转换与信号处理功能的开发

介绍了以振动/声响信号为传感器的采集对象,基于小波(包)及联合时频信号处理和模糊神经网络分类的多用途智能故障诊断系统中的实时数据采集、信号分析与识别诊断等模块的程序设计与实现.作者所开发的实用软件包在现代汽车实时故障诊断中的成功应用证明了其理论与软件开发的正确性和有效性.这里着重介绍智能故障诊断系统的数据格式转换与实时信号处理部分的设计、实现方法.     

基于时频分析与神经网络的实时智能故障诊断系统的软件设计--总体构架与实时数据采集功能的开发

介绍了以振动/声响信号为传感器的采集对象,基于小波(包)及联合时频信号处理和模糊神经网络分类的多用途智能故障诊断系统中的实时数据采集、信号分析与识别诊断等模块的程序设计与实现.作者所开发的实用软件包在现代汽车实时故障诊断中的成功应用证明了其理论与软件开发的正确性和有效性.这里着重介绍智能故障诊断系统的软件框架的设计以及实时数据采集部分的设计、实现方法.