Neural network-based flight control systems: Present and future

As the first review in this field, this paper presents an in-depth mathematical view of Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural networks. The rapid evolution of IFCSs in the last two decades in both the methodological and technical aspects necessitates a comprehensive view of them to better demonstrate the current stage and the crucial remaining steps towards developing a truly intelligent flight management unit. To this end, in this paper, we will provide a detailed mathematical view of Neural Network (NN)-based flight control systems and the challenging problems that still remain. The paper will cover both the model-based and model-free IFCSs. The model-based methods consist of the basic feedback error learning scheme, the pseudocontrol strategy, and the neural backstepping method. Besides, different approaches to analyze the closed-loop stability in IFCSs, their requirements, and their limitations will be discussed in detail. Various supplementary features, which can be integrated with a basic IFCS such as the fault-tolerance capability, the consideration of system constraints, and the combination of NNs with other robust and adaptive elements like disturbance observers, would be covered, as well. On the other hand, concerning model-free flight controllers, both the indirect and direct adaptive control systems including indirect adaptive control using NN-based system identification, the approximate dynamic programming using NN, and the reinforcement learning-based adaptive optimal control will be carefully addressed. Finally, by demonstrating a well-organized view of the current stage in the development of IFCSs, the challenging issues, which are critical to be addressed in the future, are thoroughly identified. As a result, this paper can be considered as a comprehensive road map for all researchers interested in the design and development of intelligent control systems, particularly in the field of aerospace applications.     

宁夏宁东供水工程主机设备形式参数选择与国际招标

宁东供水工程供水水泵共有卧式和立式离心泵2种方案可供选择,也是工程论证时争论的焦点,经综合比较及主机设备的国际招标,最终确定了奥地利安德里兹公司的卧式双吸中开式离心泵为宁东供水工程的供水水泵。     

三峡三期工程主坝大体积混凝土内部温度控制

三峡右岸三期工程施工中,为了有效控制坝体大体积混凝土内部温升,采取了高温季节使用预冷混凝土浇筑、控制混凝土出机口温度及浇筑温度、对混凝土内部人工通水进行初冷、中冷和后冷等措施。三峡三期工程大坝混凝土内部温度没有出现超标现象,混凝土温控工作取得了良好的效果。     

长江重要堤防隐蔽工程建设投资对扩大内需、拉动经济的作用和影响

长江重要堤防隐蔽工程是党中央、国务院实施积极财政政策进行长江堤防建设的重要组成部分，隐蔽工程既是重要的基础设施，也是重要的环境保护工程，隐蔽工程与其他行业的关联性很强，对众多行业具有巨大的带动作用，有效地扩大了内需，拉动了经济增长。     

南水北调西线工程可调水量分析

在受水区缺水形势严峻的情况下，引水工程可调水量的确定主要与三个因素有关：一是引水河流及引水坝址径流量；二是坝址上下游用水要求；三是引水水库工程规模。在考虑各种因素影响后，提出各引水坝址可调水量占坝比径流量的比例在70％左右比较合适，按现阶段推荐的两种方案，可调水量可达160亿－170亿m^3.     

马家河水电站的设计

马家河水电站通过在马家河和毛家河上游分别建底栏栅坝和低拱坝 ,经各自的引水系统将水引至两河口汇合流入前池发电。本文介绍了电站的开发方案 ,厂区、引水工程和取水枢纽的布置和设计     

Learning to Perceive and Act by Trial and Error

This article considers adaptive control architectures that integrate active sensory-motor systems with decision systems based on reinforcement learning. One unavoidable consequence of active perception is that the agent's internal representation often confounds external world states. We call this phoenomenon perceptual aliasingand show that it destabilizes existing reinforcement learning algorithms with respect to the optimal decision policy. We then describe a new decision system that overcomes these difficulties for a restricted class of decision problems. The system incorporates a perceptual subcycle within the overall decision cycle and uses a modified learning algorithm to suppress the effects of perceptual aliasing. The result is a control architecture that learns not only how to solve a task but also where to focus its visual attention in order to collect necessary sensory information.     

周宁水电站土建工程合同管理

合同管理是建设工程项目管理的一项重要内容。周宁水电站建设单位通过加强工程招标、合同变更处理、索赔处理、工程价款审核与支付及竣工结算等方面的管理工作,使土建工程造价得到了控制,同时也保证了工程进度、质量目标的实现。     

美国钢铁企业的并购浪潮及特点分析

介绍了最近美国大型钢铁企业发生的主要并购活动。并对这些并购活动的特点进行了分析。     

减少地下工程支护喷射混凝土回弹量的措施

介绍了水布垭地下厂房喷射混凝土室内试验结果和施工实践,总结了降低喷射混凝土回弹率的主要措施。