基于嵌入式动态能耗平衡的汽车节能调度算法

研究汽车嵌入式发动机的节能控制问题,由于汽车在启动过程中,发动机燃烧不充分,会造成电动机的启动电流过大,并且包含高噪声,使得汽车的动态非必要能耗增加.传统的限流限压调节算法的频率固定,很难做到真正的动态调节,不能适应非线性的大规模变化.为提高节能效果,提出了一种嵌入式动态能耗平衡的汽车节能调度算法.根据动态平衡相关理论,获取汽车运行过程中发动机的动态能耗关系,并为汽车发动机节能调度提供准确的数据.仿真结果表明,建立多核嵌入式汽车发动机任务调度模型,克服了传统算法中频率固定的弊端,说明改进算法能够有效降低汽车调度过程中的能源消耗.     

飞行器偏角和倾斜角控制优化算法的仿真分析

无人驾驶的飞行器在偏角和倾斜角控制过程中,角度控制的滞后性问题一直无法解决,高速飞行使得飞行器角度控制再入过程中的动压、过载、热流等物理约束过程复杂化,利用传统的PID飞行参数控制方法对飞行器进行控制,为了保证精度,仅仅通过改变航向角的方式来进行转弯偏角和倾斜角控制,导致转弯半径很大,无法保障控制精度.提出利用改进PID神经网络算法的飞行器偏角和倾斜角控制优化模型.根据飞行器控制系统及动力学原理获取飞行过程的动力方程,构建飞行器角度控制数学模型,根据改进后的PID神经网络算法进行最优角度值求解,降低控制系统的跟踪误差、保证算法的收敛性,实现飞行器角度控制模型的优化.实验结果表明,利用改进算法进行飞行器控制模型的优化,能够保证飞行器飞行过程的航偏角和倾斜角控制精度.     

基于队列行驶的混合动力汽车节能预测控制方法研究

针对传统混合动力汽车控制方法不考虑队列行驶对车辆能量管理影响的问题,本文提出了基于队列行驶的混合动力汽车节能预测控制智能优化策略。通过建立混合动力汽车系统的降阶模型,并采用连续广义最小残量方法求解模型预测控制问题。运用计算机进行仿真,仿真结果验证了系统模型的有效性,以及所设计的模型预测控制算法大幅度提高混合动力汽车的燃油经济性的能力和实时控制性能。     

基于深度强化学习的网联车辆队列纵向控制

针对车辆队列中多目标控制优化问题,研究基于强化学习的车辆队列控制方法.控制器输入为队列各车辆状态信息以及车辆间状态误差,输出为基于车辆纵向动力学的期望加速度,实现在V2X通信下的队列单车稳定行驶和队列稳定行驶.根据队列行驶场景以及采用的间距策略、通信拓扑结构等特性,建立队列马尔科夫决策过程(Markov decision process,MDP)模型.同时根据队列多输入-多输出高维样本特性,引入优先经验回放策略,提高算法收敛效率.为贴近实际车辆队列行驶工况,仿真基于PreScan构建多自由度燃油车动力学模型,联合Matlab/ Simulink搭建仿真环境,同时引入噪声对队列控制器中动作网络和评价网络进行训练.仿真结果表明基于强化学习的车辆队列控制燃油消耗更低,且控制器实时性更高,对车辆的控制更为平滑.     

汽车行驶稳定性动力学优化控制仿真研究

汽车行驶稳定动力学优化控制,旨在通过确定汽车行驶状态下纵向车速、横摆角速度、质心侧偏角等重要的状态变量,提前预知汽车未来时刻的可能的行驶状态,并将其输送到汽车底盘主动控制系统,实现动力学优化控制,提高汽车的主动安全性,减少道路交通事故.寻找一种低成本、高精度且能够实时获得车辆重要状态参数的方法,是汽车稳定行驶动力学优化控制的关键技术之一.利用Madab/Simulink仿真工具,分别建立了汽车动力学仿真模型和车辆行驶状态Kalman滤波估计仿真模型,可以同时实现对车辆行驶状态的仿真和对车辆行驶过程中横摆角速度、侧向加速度和质心侧偏角的估计,并且模型具有可扩展性.最后进行了实车场地试验,完成了阶跃曲线、双移线等操作,通过模型仿真、试验数据和状态估计结果的比较得出,三者一致性较好,同时验证了车辆动力学仿真模型和状态估计算法仿真模型的有效性和通用性.     

液压混合动力履带车辆联合制动模糊控制

针对液压混合动力履带车辆联合制动系统,为了实现制动过程平稳性,提出了基于制动力分配原则的模糊控制策略.首先在MATLAB中建立了能量再生制动系统和机械制动系统以及车辆动力学仿真模型,然后设计了以制动力分配系数为控制变量的联合制动模糊控制器,给出了模糊控制规则,建立了控制系统仿真模型,并在不同制动强度条件下对车辆制动过程进行仿真.仿真结果表明,联合制动模糊控制系统能够有效回收制动能量,同时与PID控制相比明显改善和提高了履带车辆制动过程稳定性.     

液压挖掘机节能控制系统设计与研究

近几年,中国已经成为全球最大的挖掘机市场,但是液压挖掘机的有效能源利用率很低,造成能源的巨大浪费。为了提高挖掘机的功率利用率,通过分析分工况控制和发动机-泵功率匹配控制原理,研制了基于JRCC300控制器的液压挖掘机节能控制系统。该控制系统具备发动机电子油门控制、发动机-泵功率匹配控制等控制功能。经过装车试验证明：控制系统能够很好地适应负载的变化,使得变量泵的吸收功率与发动机的输出功率实时匹配,保证发动机转速在设定转速范围内工作。同时,挖掘机空载时发动机转速控制误差较小,响应速度快。挖掘机燃油消耗低,效率高。     

混合动力履带车辆能量分配控制策略研究

在履带车辆能量控制策略的研究中,相比于传统的履带车辆单一的动力源,混合动力履带车辆是多能源动力系统,能量分配控制策略制约着动力系统的运行效率.为了优化能量分配控制以及改善整车的燃油经济性,提出了在发动机多点转速下,采用模糊控制理论的动力系统功率分配控制策略;建立了面向控制的整车动态仿真模型,包括驾驶员模型,动力电池组模型,发动机模型,电机模型以及整车动力学模型.根据建立的车辆动态模型,采用模糊分配控制策略,在不同的SOC初值、不同的循环工况以及不同的控制策略下仿真,结果表明,利用模糊规则的能量分配控制策略燃油经济性较好,并且能保持动力电池组SOC平衡在在一定范围内.     

基于计算机视觉技术的车辆远程控制技术研究

随着信息技术的发展,车辆远程控制成为了学术界的前瞻性研究。此次研究在合理利用计算机视觉技术的基础上,结合模糊PID控制智能算法建立了车辆远程控制系统,以期实现对车辆装置的实时监控,能够在危险状况发生时通过远程控制中心操控车辆。实验中,以履带车辆作为研究对象,对其相关参数进行了设计,以达到验证该控制系统有效性的目的。研究表明,无论是在直线行驶作业下还是曲线行驶作业下,相较于基于模糊PID控制算法的车辆控制系统,PID车辆控制系统均调节震荡大、调节时间长;而基于BP神经网络算法的车辆控制系统也存在诸多问题;因而基于模糊PID控制算法的车辆控制系统调控精度较高,适用性较强。此次研究对车辆远程控制研究具有一定的指导价值。     

基于模糊神经网络的涡喷发动机控制系统设计

针对微型涡喷发动机ECU控制系统具有时变性和非线性的特点,为改善微型涡喷发动机控制系统的控制性能,将模糊神经网络PID控制方法应用于ECU的转速与推力控制系统中;首先,利用某微型涡喷发动机的试车数据通过系统辨识方法得到其数学模型,其次针对模糊PID无法在线调参的弊端,引入模糊神经网络控制方法对微型涡喷发动机ECU系统进行控制;为模拟发动机在工作过程中遇到的干扰问题,在仿真过程中加入了干扰信号,通过与传统PID、模糊PID的仿真结果对比验证得出,模糊神经网络PID在涡喷发动机转速控制系统中响应速度更快约为1 s,超调量更小约为0,在有干扰的情况下恢复稳定状态的时间更短,约为0.5 s。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.