扰动补偿控制—减弱噪声对跟踪系统引起的误差

来自于通讯或测试系统中的噪声和外界环境干扰,对控制系统可转化为一种随机起伏的电信号,噪声对于信息的传输和处理有很大影响.对噪声的来源及如何在控制系统中消除进行了分析,并引入扰动补偿后对控制系统进行仿真,结果表明:扰动补偿控制可以减弱噪声对跟踪系统引起的误差.     

生产成本依赖规模经济效应的供应链需求扰动管理

分析了一个供应商和一个零售商组成的供应链中,供应商单位生产成本依赖规模经济效应,需求发生扰动带动单位生产成本随之发生变化时,集中控制下供应链的扰动管理策略和分散决策下供应链的协调机制;也探讨了供应商对扰动没有反应时的供应链协调机制.研究发现,扰动幅度不大时,原生产计划具有一定的鲁棒性;当扰动幅度较大时,需要同时调整价格和订货量,即采用不同的数量折扣策略协调供应链.同时,引入算例进行数值分析,结果表明,只要供应商能够对扰动作出反应,就能够使自身利润增加、供应链得到协调.     

供应中断和需求扰动下供应链竞合关系研究

考虑供应中断和需求扰动情境下2个供应商和1个零售商组成的两级供应链系统,构建了合作、静态非合作、嵌套式静态非合作3个博弈模型,分析集中式、分散式供应商竞争与合作情形下的零售商采购策略与供应商定价策略。研究表明,当市场需求增大时,分散式供应商合作情形下供应链整体利润最高;当市场需求减少时,集中式供应链整体利润最高。当权衡供应商订货成本与产品供应稳定性时,零售商倾向与相对稳定的供应商合作;当供需同时不确定时,仅较稳定的供应商受影响。     

扰动跟踪控制系统设计与仿真

在 60 Nm间随机变化的扰动力矩作用于一个实际设备的控制系统时,对其引起的跟踪误差作了仿真分析。并在研究扰动引起的稳态误差、系统结构及和参数之间关系的基础上,设计了控制系统的扰动补偿器。对扰动补偿控制系统进行了仿真,结果表明,扰动补偿控制可以减小或消除风力矩扰动引起的跟踪误差。     

跟踪系统中多闭环控制模式的分析和实现

实现高精度跟踪,尤其在外界干扰力矩下,必须增加系统刚度来提高系统的扰动抑制能力.提出将加速度反馈引入常规的跟踪系统控制方式中,实现了由电流环、加速度环、速度环、位置环构成的四闭环控制模式.高增益的加速度反馈为系统提供一个响应更快、带宽更宽的内环,克服了单纯速度反馈带宽窄的特性.首先从理论上分析和证明了该方法的意义,多闭环控制模式可以提高系统的刚度,从而增强系统的抗扰动能力;同时,在加速度反馈的基础上研制前馈控制器,能够进一步提高大速度目标的跟踪性能.在某一实际的系统中对多闭环控制模式进行了实验验证,结果表明:同以往的控制方法相比扰动抑制带宽由15 Hz 提高到30 Hz ;并且在10 Hz 以下频率获得了-30 dB 抑制能力.     

基于扰动观测器的铆接机器人轨迹跟踪控制

为解决铆接机器人工作时外部干扰造成系统抖震大,轨迹跟踪精度较低问题,设计一种扰动观测器与分数阶滑模控制器组合的自适应控制方法。首先,通过引入时延估计策略建立铆接机器人的局部动力学模型,利用扰动观测器实时观测系统模型所受的可见干扰;其次,针对系统产生的抖震问题,设计分数阶滑模面替代传统滑模控制,采用新型趋近律使系统在切换面上能够连续平稳运动,针对系统所受的不可见干扰,设计自适应策略实现对外部干扰的完全补偿;最后,通过Lyapunov函数证明所设计控制器的有效性。以三自由度机器人进行仿真及实体试验,结果表明,相较于分数阶滑模控制,采用该控制器后机器人各关节的追踪误差峰值分别下降了50%,59%和63%,从而验证了该控制器不仅能有效消除系统所受较大干扰产生的抖震问题,而且提高了铆接机器人作业时的鲁棒性和轨迹跟踪精度。     

基于误差的观测器在光电跟踪系统中的应用

对于光电跟踪系统来说,图像传感器例如电荷耦合器件(CCD)只能够探测脱靶量即偏差信息,而无法得到目标运动轨迹,所以,大多数情况下在目标跟踪回路不能直接实现前馈控制,这限制了系统的闭环跟踪性能。本文采用了一种基于误差观测器的等效前馈控制方法来提高运动平台光电跟踪系统的跟踪性能。该方法是在原有的反馈控制回路的基础上加入一个观测前馈通路,通过优化前馈滤波器提高闭环性能。由于是基于最终的视觉误差的观测,该方法对目标跟踪和扰动抑制同时起作用,既可以应用到地基跟踪也可以应用于运动平台上。前馈滤波器没有采用简单的一阶低通滤波器而是选择Q₃₁滤波器。仿真和实验表明,与传统控制方法相比,这种基于误差观测器的控制方法能够有效提高系统的低频跟踪性能。

     

多风险干扰下供应链系统的最优控制策略

文献[1]讨论了一类受需求风险干扰的供应链系统最优控制策略,而供应链在运作过程中可能同时受到多个风险因素的干扰。本文在文献[1]的基础上,考虑供应链系统同时受到需求风险和交货延迟风险的干扰,构建了供应链系统状态方程模型,引入前馈反馈最优控制理论来实现供应链系统的最优控制策略。在讨论了无法求取系统最优控制律时,给出了系统的M阶次优控制律,并设计了一类迭代算法对模型进行了求解。通过对算例的计算与仿真,验证了该次优控制策略对需求风险和交货延迟风险的干扰具有明显的抑制作用,使得供应链系统在受扰情况下能持续稳定地运作。     

多时滞无线通信网络的功率和速率最优跟踪

研究了无线通信网络的功率和速率控制这一热点问题。针对传统的无线通信网络模型并没有同时考虑状态时滞和输入时滞,已有的功率和速率控制算法也不能保证系统具有最优输出跟踪性能的情况,重新建立了无线通信网络的模型,在建模过程中考虑了多时滞,得到了含有不同的状态时滞和输入时滞的功率和速率控制系统模型,在此基础上,研究了一般形式的多时滞模型的时滞补偿算法,并将该算法应用在提出的多时滞模型中,给出了无线通信网络功率和速率的最优跟踪控制律。经过计算机仿真验证,提出的最优控制律具有良好的控制性能。     

前馈控制的神经网络实现

不依赖对象模型,在前馈－反馈定值控制系统中,借助神经网络构成前馈控制器,以反馈输出引导网络权值及输出的调整,使网络逐步学成前馈补偿功能,并最终在控制中占据主导地位,实现对主要可测干扰的补偿。文章分析了神经网络前馈控制器的作用效果,并与根据精确模型设计的常规前馈控制器的作用特性进行了比较。文中采用两种不同方式对神经网络进行训练,仿真结果证实了在模型未知的条件下,利用神经网络实现前馈控制的有效性。     

Coordinating a three-layer supply chain with uncertain demand and random yield

The paper considers a three-layer supply chain involving one raw-material supplier, one manufacturer and one retailer. The market demand is assumed to be stochastic and productions at the raw-material supplier and manufacturer are subject to random yield. The centralised model is studied as the benchmark case. The decentralised model is solved and Nash equilibrium solutions are obtained. It is shown that buyback contract fails to coordinate such a supply chain. However, a composite contract framed combining buyback, and sales rebate and penalty contracts is shown to coordinate the supply chain. Numerical examples are provided to illustrate the developed models.     

含控制时滞的海洋平台前馈反馈最优跟踪控制

通过引入状态变换,将含控制时滞的海洋平台系统转化为无时滞系统.然后,通过引入渐近稳定的期望系统,基于波浪力线性外系统近似模型,给出了海洋平台系统基于二次型性能指标泛函的前馈反馈最优跟踪控制器设计方法及其控制器的存在唯一性条件.控制器的前馈增益矩阵和反馈增益矩阵可分别经由求解代数Riccati方程和Sylvester方程得到.仿真算例表明了方法的有效性,且在减小平台的振动幅值和控制力方面,前馈反馈最优跟踪控制方法优于前馈反馈最优控制方法.     

Integrating packaging suppliers into the supply/demand chain

This paper presents the results from qualitative studies done on leading‐edge companies in supply/demand chain management in Sweden. The aim of the study was to create a knowledge base, identify the network integrators and, with reference to previous studies conducted in the packaging industry, analyse the development for packaging suppliers. Copyright © 2005 John Wiley & Sons, Ltd.     

Managing demand uncertainty through fuzzy inference in supply chain planning

In this paper, we investigate methods for managing the irregular and uncertain demands involved in supply chain planning. We first build a supply chain planning model based on fuzzy linear programming, which defines demand as a fuzzy parameter. Next, we propose a fuzzy inference approach for converting fuzzy demand into crisp demand. In the proposed fuzzy inference-based approach, judgments of upcoming demand from both internal and external experts are used as input variables to reflect the expected demand irregularity. By adopting fuzzy inference, we can compensate for the limitations of the existing demand treatment approaches, which usually demonstrate poor forecasting performance in cases of irregular demand and thus reduce the accuracy of supply chain planning. To verify the feasibility of the proposed approach, we present an illustrative example of a Korean electronics company.     

A simulation-optimisation approach for supply chain network design under supply and demand uncertainties

We investigate a three-echelon stochastic supply chain network design problem. The problem requires selecting suppliers, determining warehouses locations and sizing, as well as the material flows. The objective is to minimise the total expected cost. An important feature of the investigated problem is that both the supply and the demand are uncertain. We solve this problem using a simulation-optimisation approach that is based on a novel hedging strategy that aims at capturing the randomness of the uncertain parameters. To determine the optimal hedging parameters, the search process is guided by particle swarm optimisation procedure. We present the results of extensive computational experiments that were conducted on a large set of instances and that provide evidence that the proposed hedging strategy constitutes an effective viable solution approach.     

Vendor managed inventory with consignment stock for supply chain with stock- and price-dependent demand

This paper presents a single vendor–single buyer coordinated model. The vendor produces a single deteriorating item and transfers it to the buyer in equal shipments. The model is based on vendor managed inventory with consignment stock (VMI-CS) agreement in which the vendor uses the buyer’s warehouse. The buyer stocks items both on his shelf and in his warehouse. The demand is assumed to be linearly sensitive to inventory level and selling price. The objective is to determine variables that maximise the total profit. An exact solution procedure is proposed to find the optimal solution. Numerical results show that supply chain members will benefit from the advantages of economies of scale in coordinated model with VMI-CS policy.     

Coordinating a supply chain under uncertain demand and random yield in presence of supply disruption

A two-echelon supply chain involving one manufacturer and one retailer for a single product is considered in this paper. The end customers’ demand is assumed to be random. The production of the manufacturer is subject to random yield, and there is a possibility of supply disruption in which case no item from her can reach the retailer. The retailer has a backup supplier who is costlier but perfectly reliable, and is having a limit up to which he may deliver. In addition to placing an order to the manufacturer, the retailer is allowed to reserve a quantity from the backup supplier in the ordering period; he may buy up to the reserved quantity after realising actual market demand in the trading period. Aiming at studying the effects of the various uncertainties involved in the chain on the optimal decisions, we develop and analyse centralised and decentralised models. We also propose a contract mechanism to coordinate the chain and find threshold conditions for which the coordinated model would collapse. Numerical examples are provided to illustrate the developed model.     

Optimal pricing strategy for the perishable food supply chain

This research investigates the optimal pricing strategy for the perishable food supply chain. Using the setting of a two-echelon supply chain including a supplier and a retailer, we apply the game theory approach to derive the equilibriums for both a single pricing strategy and a two-stage pricing strategy. Through a comparison of the equilibriums, we explore how the two pricing strategies affect the supply chain’s decisions and supplier’s and retailer’s performance individually and collectively. The results of the analysis show that the optimal choice of pricing strategy depends on the price markdown cost and its relationship with the two critical thresholds that are determined by a combination of factors including the potential market size, the price and quality sensitivity factors, the initial quality, the unit product cost, and the quality deterioration rate.     

Pricing and effort decisions for a supply chain with uncertain information

This paper analyses the pricing and effort decisions of a supply chain with single manufacturer and single retailer. The manufacturer produces a kind of product and then wholesales the product to the retailer, who in turn retails it to customers over a single selling season. The retailer can influence demand through her sales effort. This research depicts the consumer demand, the manufacturing cost and the sales effort cost as uncertain variables. Considering the demand expansion effectiveness of sales effort, one centralised and three decentralised game models are built on the basis of the expected value criterion, and the equilibrium solutions are obtained. We investigate the effects of the parameters’ uncertainty degrees on the pricing and effort decisions. The results indicate that the manufacturer benefits from improvement in demand and cost uncertainties when he has at least bargaining power in the supply chain. The results also imply that the uncertainty degree of sales effort elasticity has an outstanding influence on the pricing and effort decisions, whereas the uncertainty degree of price elasticity has a modest impact on these decisions. We also study the effects of the parameters’ uncertainty degrees on the supply chain from the consumers’ perspective. The results suggest that with a power retailer, the retail price should always be on the high end. Consequently, consumers do not necessarily benefit from a power retailer. When the manufacturer and the retailer have equal bargaining power, consumers do not necessarily benefit from the supply chain, either.     

Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility

The paper examines the mediating effect of supply chain (SC) practices on the relationship between agile supply chain (ASC) strategy and SC performance. It further examines the moderating effect of information systems (IS) capability for agility on this mediated relationship. Using the theoretical lenses of complementarity and the information processing view of the supply chain, we hypothesise that strategic supplier partnership, customer relationship, postponement and lean practices, mediate the relationship between ASC strategy and SC performance. We further hypothesise that IS capability for agility moderates each of these mediated relationships. We empirically test the hypotheses using survey data from members of senior and executive management in the logistics/supply chain functions of 205 firms. The paper contributes to the literature on ASCs by theoretically explaining and empirically demonstrating how SC practices and IS capability for agility act together to effect a positive relationship between ASC strategy and supply chain performance.