Robust adaptive control for greenhouse climate using neural networks

This paper presents a general framework for robust adaptive neural network (NN)‐based feedback linearization controller design for greenhouse climate system. The controller is based on the well‐known feedback linearization, combined with radial basis functions NNs, which allows the feedback linearization technique to be used in an adaptive way. In addition, a robust sliding mode control is incorporated to deal with the bounded disturbances and the approximation errors of NNs. As a result, an inherently nonlinear robust adaptive control law is obtained, which not only provides fast and accurate tracking of varying set‐points, but also guarantees asymptotic tracking even if there are inherent approximation errors. Copyright © 2010 John Wiley & Sons, Ltd.     

An enhanced model framework of personalized material flow services

A growing concern about the consumer behavior in Internet economy has spurred the study of Material Flow, resulting in a unique type of consumer behavioral analysis. This research proposes an enhanced conceptual model for Personalized Material Flow Services for consumer behavior. In the era of Internet information technology, customer’s taste tends to be personalized for their market demand. It is observed that there are number of “Long Tail” phenomena in several successful e-commerce business cases. However, the Long Tail phenomenon is an open question for our research in terms of its role in e-commerce marketing. In the proposed model-X-Party Personalized Material Flow Services, three elements are discussed. They are “providing”, “locating” and “obtaining” based on X-Party Material Flow theory for which the concept of virtual collector, information filter and Material Flow coordinator are discussed. Business examples of Amazon, Dangdang and Taobao are used to analyze the elements of the virtual collector, information filter and Material Flow coordinator of the Personalized Material Flow Service system.     

Fire detection algorithms for video images of large space structures

In large space structures, the latest fire detection methods are based on video image processing and data fusion. But the false positive rate and false negative rate remain unsatisfactory and need improving. The emphases of this paper are target extraction and recognition. A new adaptively updating target extraction algorithm (NAUTEA) is proposed by which the intact target can be extracted in time. In addition, some fire video image recognition algorithms, such as fuzzy neural network (FNN) and FGALSSVM (Fuzzy GALSSVM), are studied and improved. To verify the performance of these algorithms, a prototype system is developed, and a series of algorithm tests on a fire video are conducted. These tests make it clear that, the accurate, robust and real-time fire detection can be realized.     

一种新型监狱使用的物联网节点设计

一种新型智能手铐作为物联网的节点,其主要利用指纹和电子滚码通过优先级进行开关锁来加强安全性,并且通过上位机能够实时地监控手铐的开关状态;同时加上了GPS定位功能,由上位机监控节点所在的位置和移动轨迹,并且系统每小时做一次监测结果备份,监察员可以调用任意时间段的数据.这种新型手铐运用物联网技术便于对犯人进行统一管理和监控,减轻了监狱监控管理人员的负担,并且在犯人逃跑过程中可以起到有效跟踪追捕功能.主要介绍了系统的整体架构、软硬件设计技术和系统功能.     

基于自适应遗传算法的测试用例生成工具

提出一种“对组合”测试用例生成算法。给出“对组合”索引表的概念。在索引表的基础上,实现一种自适应遗传算法生成测试用例集合。介绍使用该方法开发的测试用例自动生成工具GATG。实验证明,该方法基本达到国际同类工具的平均水平,具有较好的使用价值和应用前景。     

基于改进遗传算法的TD-SCDMA扇区优化

获得满意的覆盖是TD-SCDMA标准网络规划的重点,为此,在遗传算法的基础上提出基于PCCPCH RSCP覆盖和PCCPCH C/I覆盖的改进遗传算法。采用符合网络多扇区多参数性质的二进制矩阵式编码,为加快收敛速度,给出基于块的交叉方法,同时为防止过早的局部收敛,对适应度函数进行尺度变换。实验结果表明,该算法可以快速收敛到目标解,PCCPCH RSCP覆盖比例和PCCPCH C/I覆盖比例均有不同程度的提升。     

基于Tibco BusinessWorks的Web服务的设计与实现

Web服务技术作为一种全新的分布式技术和网络资源共享技术已被广泛研究和使用,Tibco公司的产品BusinessWorks是用于设计实现Web服务的工具。通过BusinessWorks对Web服务的完整支持,为企业级Web服务应用提供了灵活的系统框架和完整的解决方案。在车险公估系统中,使用BusinessWorks代替传统的Axis开发Web服务,既可以快捷有效地实现配件价格共享功能,又能够提高Web服务的性能。     

基于GPRS的油井远程监控系统设计

针对当今油井现场作业情况监控的缺陷,研究、设计并实现了基于GPRS模块的油井远程监控系统。系统综合应用了先进MCGS工控组态软件、GPRS模块、信号检测与处理等技术对油井现场进行了有效地监控,能对各种数据进行方便地统计和查询。通过模拟调试验证了结合上位机和下位机对油井大钩负荷、原油油管压力和油管内原油温度的远程监测和现场监控。     

嵌入式疲劳驾驶监测系统的设计与实现

疲劳驾驶是引发恶性交通事故的重要原因之一,驾驶员疲劳监测技术近年来已逐步成为图像处理领域的一个研究热点。基于改进的和提出的新算法,设计了一个嵌入式驾驶员疲劳监测系统。由可见光/近红外摄像头采集视频,首先采用Haar特征的级联分类器从图像中检测出人脸区域,并用钻石搜索法跟踪人脸区域;然后提取一个新的图像差分统计特征,并结合3个准则判断疲劳状态;最后采用全变分模型消除图像中的非均匀光照,以便实现鲁棒的人眼定位和人脸识别。实验测试结果表明,本系统的疲劳状态监测准确率达到95%以上。     

水下定位系统传感器安装误差标定技术研究

提出了一种基于非线性参数估计的水下定位系统传感器安装误差标定技术.水下定位系统由声学传感器,GPS和船体姿态传感器组成,各传感器的坐标系并不能完全重合,需要对传感器之间的误差标定后进行修正才能够获得高精度的定位效果.已有的标定方法多基于高斯-牛顿迭代法,而当非线性系统模型线性化带来较大误差时,常规的基于高斯-牛顿迭代法的标定方法已无法达到高精度的要求,而非线性模型参数估的直接解法则掺人了三阶量,有效减小线性化的模型误差,提高了各传感器安装误差的标定精度.海试数据处理表明:定位精度可由1 m提高到0.7 m.