Optimal production control of a dynamic two-product manufacturing system with setup costs and setup times

This paper deals with the optimal control of a one-machine two-product manufacturing system with setup changes, operating in a continuous time dynamic environment. The system is deterministic. When production is switched from one product to the other, a known constant setup time and a setup cost are incurred. Each product has specified constant processing time and constant demand rate, as well as an infinite supply of raw material. The problem is formulated as a feedback control problem. The objective is to minimize the total backlog, inventory and setup costs incurred over a finite horizon. The optimal solution provides the optimal production rate and setup switching epochs as a function of the state of the system (backlog and inventory levels). For the steady state, the optimal cyclic schedule is determined. To solve the transient case, the system's state space is partitioned into mutually exclusive regions such that with each region, the optimal control policy is determined analytically.     

铝电解过程控制信号的滤波与噪声解析模型的研究

将快速傅里叶变换技术和数字滤波器设计技术应用于铝电解过程控制信号的滤波与噪声解析模型中,在160kA中间点式下料预焙槽上的试验结果表明了模型的有效性。     

数据采集与光条图象细化新方法——用于三维计算机视觉系统

介绍了具有位置反馈信息旋转平台的图象数据采集方法,以及对采集到的图象进行智能化快速细化的新方法,使得在一周内的36幅图象做到边采集边细化,而且仅用40s时间。     

最优吸收截面的存在性

对被真空包围的无穷平行平板，运用勒贝格控制收敛定理和Ｃａｕｃｈｙ－Ｓｃｈｗａｒｔｙ不等式，给出稳态中子迁移系统最优吸收截面的存在性。     

几种约束广义逆矩阵的有限算法

1引言与引理众所周知，关于非奇异方阵的正则逆的有限算法是由Faddeev大给在1949年之前提出的，这就是著名的Faddeev算法[1，P…334-336]。自从五十年代中期广义逆矩阵的研究复兴与发展以来，有不少学者提出了关于广义逆矩阵的有限算法。第一个给出关于广义逆矩     

神经网络自适应滤波器在故障诊断中的应用

分析了用自适应滤波器进行故障诊断的方法．针对该方法在计算上要花费大量时间、难于完成实时诊断任务的缺点，提出了用神经网络自适应滤波器来完成故障诊断的方法．神经网络有极快的运行速度，能很好地完成实时诊断任务．     

SXDG-1型汽车前照灯全自动检测仪的微机控制

SXDG—1型汽车前照灯全自动检测仪是用于检测汽车前照大灯光轴的偏斜情况及发光强度并进行定量检验的专用设备。它可以自动测出有关参数,并予以数字显示和打印输出。本文介绍了该仪器的主要性能、工作原理及微机控制系统(包括硬件结构和软件设计思想等)。     

字节全加器及其在无线电测控系统中的应用

对全加器概念进行了推广，并在此基础上给出了使用字节全加器网络的无线电抗干扰算法。通过在实际的无线电测控系统中的应用，结果表明该算法具有良好的无线电抗干扰效果。     

On the departure process of a leaky bucket system with long-range dependent input traffic

Due to the strong experimental evidence that the traffic to be offered to future broadband networks will display long-range dependence, it is important to study the possible implications that such traffic may have for the design and performance of these networks. In particular, an important question is whether the offered traffic preserves its long-range dependent nature after passing through a policing mechanism at the interface of the network. One of the proposed solutions for flow control in the context of the emerging ATM standard is the so-called leaky bucket scheme. In this paper we consider a leaky bucket system with long-range dependent input traffic. We adopt the following popular model for long-range dependent traffic: Time is discrete. At each unit time a random number of sessions is initiated, having the distribution of a Poisson random variable with mean λ. Each of these sessions has a random duration τ, where the integer random variable τ has finite mean, infinite variance, and a regularly varying tail, i.e., P(τ >К) ~ К^-Lα L(К), where 1 < α < 2 L(·) is a slowly varying function. Once a session is initiated, it generates one cell at each unit of time until its termination. We examine the departure process of the leaky bucket policing mechanism driven by such an arrival process, and show that it too is long-range dependent for any token buffer size and any - finite or infinite - cell buffer size. Moreover, upper and lower bounds for the covariance sequence of the output process are established. The above results demonstrate that long-range dependence cannot be removed by the kinds of flow control schemes that are currently being envisioned for broadband networks. This revised version was published online in June 2006 with corrections to the Cover Date.     

GDDP: Generalized Dual Dynamic Programming Theory

This document presents theoretical considerations about the solution of dynamic optimization problems integrating the Benders Theory, the Dynamic Programming approach and the concepts of Control Theory. The so called Generalized Dual Dynamic Programming Theory (GDDP) can be considered as an extension of two previous approaches known as Dual Dynamic Programming (DDP): The first is the work developed by Pereira and Pinto [3–5], which was revised by Velásquez and others [8,9]. The second is the work developed by Read and others [2,6,7].