应用于控制领域的黑板结构

本文主要研究智能控制系统的框架结构问题。首先总结了黑板模型的两个本质特征,然后分析了控制领域问题求解的特点及其对黑板模型的适用性。在此基础上,提出一种能使控制领域的问题求解与控制作用相结合的黑板结构,并给出了一个基于该结构的应用实例。     

Intelligent Cooperative Control for Urban Tracking

We introduce an intelligent cooperative control system for ground target tracking in a cluttered urban environment with a team of autonomous Unmanned Air Vehicles (UAVs). We extend the work of Yu et al. to use observations of target position to learn a model of target motion. Simulated cooperative control of a team of 9 UAVs in a 100-block city filled with various sizes of buildings verifies that learning a model of target motion can improve target tracking performance.     

基于多主体的楼宇智能控制体系结构

该文提出了一种基于多主体系统的楼宇智能控制体系结构。该体系结构以房间作为基本的逻辑控制单位,其中控制设备的互联基于BACnet协议,然后通过BACnet路由器路由到以太网;多主体系统驻留在以太网的工作站上,从结构上划分为网络层、中间件层、应用层、用户层,其中中间件层使上层的控制应用不依赖于底层语义;为支持系统的互操作性及与未来应用的兼容性,多主体系统基于FIPA标准参考模型实现。     

A Framework for Distributed Semi-supervised Learning Using Single-layer Feedforward Networks

Machine Intelligence Research - This paper aims to propose a framework for manifold regularization (MR) based distributed semi-supervised learning (DSSL) using single layer feed-forward neural...     

智能协作控制系统

提出了智能协作控制系统的框架、原理,并介绍了设计方法。建立了基于产生式规则的黑板结构多智能体控制系统,采用多智能体联合问题求解策略,对不同的外部环境(被控对象),具体设计方法有：任务分配,子问题求解,结果综合,控制级设计。对子问题求解中产生的冲突或无解,如何进行结果综合,以达到最优或次优,是采用重新分配任务,还是更改知识库,或推理方法等有待进一步探讨。     

Distributed Cooperative Control for Adaptive Performance Management

The authors' distributed cooperative-control framework uses concepts from optimal control theory to adaptively manage the performance of computer clusters operating in dynamic and uncertain environments. Decomposing the overall performance-management problem into smaller subproblems that individual controllers solve cooperatively allows for the scalable control of large computing systems. The framework also adapts to controller failures and allows for the dynamic addition and removal of controllers during system operation. This article presents a case study showing how to manage the dynamic power consumed by a computer cluster processing a time-varying Web workload     

A Unified Adaptive Iterative Learning Control Framework for Uncertain Nonlinear Systems

In this note, we propose a unified framework for adaptive iterative learning control design for uncertain nonlinear systems. It is shown that if a Lyapunov based adaptive control law is available for the system under consideration and the Lyapunov function satisfies certain conditions, it is straightforward to extend the adaptive controller to handle repetitive systems operating over a finite time interval. According to the value of a certain parameter gamma, the parametric adaptation law can be a pure time-domain adaptation, a pure iteration-domain adaptation or a combination of both.A pure iteration-domain adaptation is described by a difference equation, a pure time-domain adaptation is described by a differential equation, and a combination of both is described by a differential-difference equation. The advantages and disadvantages of the three possible adaptation types are discussed and some illustrative examples are given. [All rights reserved Elsevier].     

基于CMAC神经网络的智能助行机器人在线学习控制

为了使老年人能够独立、安全、舒适地行走于户外环境,针对自行开发的智能助行机器人ZJU Walker,提出一种基于CMAC神经网络的在线学习控制算法.CMAC神经网络模拟人的小脑结构,具有学习速度快、结构简单等特点.采用CMAC神经网络对用户的行走习惯进行关联记忆和在线学习,并理解用户的行走意图.实验结果验证了所提方法的有效性,使助行机器人更加易于使用,提高了用户在使用过程中的舒适度.     

Performance Improvement of Robot Continuous-Path Operation through Iterative Learning Using Neural Networks

In this article, an approach to improving the performance of robot continuous-path operation is proposed. This approach utilizes a multilayer feedforward neural network to compensate for model uncertainty associated with the robotic operation. Closed-loop stability and performance are analyzed. It is shown that the closed-loop system is stable in the sense that all signals are bounded: it is further proved that the performance of the closed-loop system is improved in the sense that certain error measure of the closed-loop system decreases as the network learning process is iterated. These analytical results are confirmed by computer simulation. The effectiveness of the proposed approach is demonstrated through a laboratory experiment.     

A Framework for Robust Subspace Learning

Many computer vision, signal processing and statistical problems can be posed as problems of learning low dimensional linear or multi-linear models. These models have been widely used for the representation of shape, appearance, motion, etc., in computer vision applications. Methods for learning linear models can be seen as a special case of subspace fitting. One draw-back of previous learning methods is that they are based on least squares estimation techniques and hence fail to account for outliers which are common in realistic training sets. We review previous approaches for making linear learning methods robust to outliers and present a new method that uses an intra-sample outlier process to account for pixel outliers. We develop the theory of Robust Subspace Learning (RSL) for linear models within a continuous optimization framework based on robust M-estimation. The framework applies to a variety of linear learning problems in computer vision including eigen-analysis and structure from motion. Several synthetic and natural examples are used to develop and illustrate the theory and applications of robust subspace learning in computer vision.     

EJB体系结构性能的改进及应用

通过对J2EE/EJB的体系结构和技术规范的分析和研究,对传统的EJB体系结构进行了改进,提出了一种更适应于企业的分布式多层应用体系结构的参考模型。通过对该参考模型的深入剖析,给出了各层最佳的实现策略,从而提高了原有体系结构的可扩展性和访问效率,使J2EE/EJB多层体系结构更能适应大型的企业应用的需求。     

EJB体系结构性能的改进及应用

通过对J2EE／EJB的体系结构和技术规范的分析和研究，对传统的EJB体系结构进行了改进，提出了一种更适应于企业的分布式多层应用体系结构的参考模型。通过对该参考模型的深入剖析，给出了各层最佳的实现策略，从而提高了原有体系结构的可扩展性和访问效率，使J2EE／EIB多层体系结构更能适应大型的企业应用的需求。     

Implementing Requirements Engineering Processes: Using Cooperative Self-Assessment and Improvement

Requirements engineering can help assure success for projects and their products. Small-to-medium enterprises (SMEs) demand effective, efficient RE practice because they must adhere to delivery dates and provide the same quality as large organizations, but with a smaller budget and staff. Moreover, these companies are highly affected by each customer's specific needs, and they must react accordingly.     

基于XML/SOAP的校园Web服务体系构架

通过对Web服务系统与传统Web和EAI的比较，认为Web服务更适合于校园网建设，并因此提出一种基于XML的校园网Web服务体系架构。     

基于.NET平台的三层架构的改进设计

随着Web技术的发展,ASP.NET普通的web form控件已无法满足当前的开发需求,数据、业务及表示相分离越来越符合开发需求,MVC框架及三层架构被提出并得以广泛应用。针对.NET三层架构的实现原理进行分析,并在此基于实际开发过程进行优化处理,提出一种改进方案;其次重点对改进方案进行代码实现,同时在运维平台中验证改进方案的可行性。     

在基于Spring框架的应用中使用Acegi实现安全控制

Spring框架是一个开发J2EE应用的优秀框架，Spring本身没有提供对系统安全方面的支持。Acegi是基于Spring IOC和AOP机制实现的一个安全框架。本文探讨了Acegi安全框架中各部件的交互方法，并给出了使用Acegi安全框架实现基于Spring框架的应用的安全控制方法。     

在基于Spring框架的应用中使用Acegi实现安全控制

Spring框架是一个开发J2EE应用的优秀框架,Spring本身没有提供对系统安全方面的支持。Acegi是基于SpringIOC和AOP机制实现的一个安全框架。本文探讨了Acegi安全框架中各部件的交互方法,并给出了使用Acegi安全框架实现基于Spring框架的应用的安全控制方法。     

认知无线电中基于协同中继的网络性能优化

针对认知无线电和协同通信这两种技术的结合,在认知无线电中设计联合解码转发JDF方案,在保证主要网络链接的服务质量(QoS)的前提下,无论在峰值干扰约束还是均值干扰约束的情况下,都能得到最优解,使认知无线电用户的传输速率最大化;通过仿真分析可以得出:在认知无线电网络中,使用优化后的发射功率和恰当的协同中继进行传输能提高系统性能,优于直接传输和单独的协同传输.     

智能多媒体教学平台中关键技术的研究

智能多媒体教学平台是一个建立在CSCW理论基础上,旨在实现远程教学中多点间师生有效协作的系统。介绍了该平台的体系结构,提出了教学平台中的协同并发控制策略——基于创造者和角色的并发控制策略,并详细阐述了智能多媒体教学平台的实现及关谜技术：类隧道组播技术、混音技术、多个实时视频流的声控显示／隐藏技术。     

A Reusable Multi-Agent Architecture for Active Intelligent Websites

In this paper a reusable multi-agent architecture for intelligent Websites is presented and illustrated for an electronic department store. The architecture has been designed and implemented using the compositional design method for multi-agent systems DESIRE. The agents within this architecture are based on a generic information broker agent model. It is shown how the architecture can be exploited to design an intelligent Website for insurance, developed in co-operation with the software company Ordina Utopics and an insurance company.