DSP技术在液压混合动力汽车能源控制方面的应用

文章分析了液压混合动力汽车的发展趋势,简述数字信号处理器(DSP)作为控制器的优势和DSP作为控制器对并联式混合动力液压车的能源控制的工作原理,给出了能源控制系统DSP信号流程图和主程序流程图。测试结果表明,DSP能源控制系统能够比较精确的对液压混合动力车的能量消耗与分配进行控制,具有很好的应用前景。     

试述盐厂重要环境因素的控制

依据GB/T14001标准,阐述了制盐生产环境因素的识别,重要环境因素的评定及其控制.同时指出了消除重要环境因素的影响,保护环境是实施污染预防的有效途径.     

FHCF: A Simple and Efficient Scheduling Scheme for IEEE 802.11e Wireless LAN

The IEEE 802.11e medium access control (MAC) layer protocol is an emerging standard to support quality of service (QoS) in 802.11 wireless networks. Some recent work shows that the 802.11e hybrid coordination function (HCF) can improve significantly the QoS support in 802.11 networks. A simple HCF referenced scheduler has been proposed in the 802.11e which takes into account the QoS requirements of flows and allocates time to stations on the basis of the mean sending rate. As we show in this paper, this HCF referenced scheduling algorithm is only efficient and works well for flows with strict constant bit rate (CBR) characteristics. However, a lot of real-time applications, such as videoconferencing, have some variations in their packet sizes, sending rates or even have variable bit rate (VBR) characteristics. In this paper we propose FHCF, a simple and efficient scheduling algorithm for 802.11e that aims to be fair for both CBR and VBR flows. FHCF uses queue length estimations to tune its time allocation to mobile stations. We present analytical model evaluations and a set of simulations results, and provide performance comparisons with the 802.11e HCF referenced scheduler. Our performance study indicates that FHCF provides good fairness while supporting bandwidth and delay requirements for a large range of network loads. Pierre Ansel received a multidisciplinary in-depth scientific training in different fields such as Pure and Applied Mathematics, Physics, Mechanics, Computer Science and Economics from the Ecole Polytechnique, Palaiseau, France. Then, he joined the Ecole Nationale Superieure des Telecommunications, Paris, France in 2005 where he went further into electronics, databases, computer network security and high speed networks. He received a multidisciplinary master of sciences degree and an additional master of sciences degree in telecommunications in 2005. He did a summer internship in 2003 in INRIA, Sophia Antipolis, France where he worked on the Quality of Service in 802.11 networks at Planete Group, France. Then in 2004, he joined France Telecom R&D, Issy-les-Moulineaux, France to work on Intranet Security issues. He designed a WiFi security supervision architecture based on WiFi Intrusion Detection Sensors. He is currently a French civil servant and belongs to the French Telecommunications Corps. Qiang Ni received the B.Eng., M.Sc. and Ph.D. degrees from Hua Zhong University of Science and Technology (HUST), Wuhan City, China in 1993, 1996 and 1999 respectively. He is currently a faculty member in the Electronic and Computer Engineering Division,School of Engineering and Design, Brunel University, West London, U.K. Between 2004 and 2005 he was a Senior Researcher at the Hamilton Institute, National University of Ireland, Maynooth. From 1999 to 2001, he was a post-doctoral research fellow in the multimedia and wireless communication laboratory, HUST, China. He visited and conducted research at the wireless and networking group of Microsoft Research Asia Lab during the year of 2000. From Sept. 2001 until may 2004, he was a research staff member at the Planète group of INRIA Sophia Antipolis France. Since 2002, he has been active as a voting member at the IEEE 802.11 wireless LAN standard working group. His current research interests include communication protocol design and performance analysis for wireless networks, cross-layer optimizations, vertical handover and mobility management in mobile wireless networks, and adaptive multimedia transmission over hybrid wired/wireless networks. He has authored /co-authored over 40 international journal/conference papers, book chapters, and standard drafts in this field. He is a member of IEEE. E-mail: Qiang.Ni@ieee.org Thierry Turletti received the M.S. (1990) and the Ph.D. (1995) degrees in computer science both from the University of Nice – Sophia Antipolis, France. He has done his PhD studies in the RODEO group at INRIA Sophia Antipolis. During the year 1995–96, he was a postdoctoral fellow in the Telemedia, Networks and Systems group at LCS, MIT. He is currently a research scientist at the Planete group at INRIA Sophia Antipolis. His research interests include multimedia applications, congestion control and wireless networking. Dr. Turletti currently serves on the Editorial Board of Wireless Communications and Mobile Computing.     

汽车排放控制系统中的氧传感器现状及展望

介绍了浓差型(Nernst型)、极限电流型和半导体电阻型等汽车排放控制系统中的氧传感器原理及结构。在综合该领域国内外研究现状的基础上,对氧传感器的发展进行了展望。     

Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons

In this paper, we propose and investigate a new category of neurofuzzy networks—fuzzy polynomial neural networks (FPNN) endowed with fuzzy set-based polynomial neurons (FSPNs) We develop a comprehensive design methodology involving mechanisms of genetic optimization, and genetic algorithms (GAs) in particular. The conventional FPNNs developed so far are based on the mechanisms of self-organization, fuzzy neurocomputing, and evolutionary optimization. The design of the network exploits the FSPNs as well as the extended group method of data handling (GMDH). Let us stress that in the previous development strategies some essential parameters of the networks (such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of the specific subset of input variables) being available within the network are provided by the designer in advance and kept fixed throughout the overall development process. This restriction may hamper a possibility of developing an optimal architecture of the model. The design proposed in this study addresses this issue. The augmented and genetically developed FPNN (gFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNNs. The GA-based design procedure being applied at each layer of the FPNN leads to the selection of the most suitable nodes (or FSPNs) available within the FPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gFPNN is quantified through experimentation in which we use a number of modeling benchmarks—synthetic and experimental data being commonly used in fuzzy or neurofuzzy modeling. The obtained results demonstrate the superiority of the proposed networks over the models existing in the references.     

微机控制励磁在泵站自动化中的应用

在泵站自动控制中,微机励磁系统是非常重要的环节。分析了电机无刷励磁系统存在的问题和微机控制励磁系统的原理、性能特点。根据目前泵站应用情况,得出采用WKLF-41型微机控制无刷系统,可大大改善电机的励磁稳定和可靠性,泵站自动化性能也能得到提高。     

浆砌石衬砌在渠道防渗中的应用及对策

总结了浆砌石应用的历史,介绍了浆砌石的结构特性和施工工艺,从造价方面、防渗效果及施工三方面分析了浆砌石衬砌主要存在的问题,并提出了相应的解决对策,指出浆砌石衬砌在渠道防渗应用中应控制施工质量,从而更好地提高防渗效果。     

提高工程量清单编制质量的思考

文章从如何提高对工程量清单编制工作重要性的认识入手,分析了实现计价理念、计价侧重点和造价控制观念转变的必要性,重点阐述了提高工程量清单编制质量应给予足够重视的几个关键环节。     

On assertion-based encapsulation for object invariants and simulations

In object-oriented programming, reentrant method invocations and shared references make it difficult to achieve adequate encapsulation for sound modular reasoning. This tutorial paper surveys recent progress using auxiliary state (ghost fields) to describe and achieve encapsulation. It also compares this technique with encapsulation in the forms provided by separation logic. Encapsulation is assessed in terms of modular reasoning about invariants and simulations.     

凤滩水电厂自动发电控制策略

介绍了凤滩水电厂自动发电控制(AGC)策略的实现方法,重点介绍了修正等容量比例有功分配方法及相应措施.程序设计的原则是,机组紧跟目标负荷的情况下,在最佳效率下运行,同时减少机组开/停机次数、有功调节频率和跨越振动区次数,从而减少机组磨损,兼顾运行效率和机组运行安全.