基于输出协方差配置的车辆振动控制系统设计

通过对车辆振动系统的振动特性分析,确定出系统反馈控制的设计目标。基于对［１］中状态协方差配置控制理论的推广,文中给出了控制器设计的具体方法,并举例说明该设计方法具有直接有效的特点     

带内双频电磁辐射对频率步进连续波雷达的虚警干扰规律

为掌握带内双频电磁辐射对雷达的虚警干扰规律,以频率步进连续波雷达为研究对象,基于理论分析与效应试验,研究了虚警目标的电平变化规律、波形特征以及出现位置规律。结果表明:受试雷达在带内双频电磁辐射作用下,不考虑互调干扰时,至多产生两个位置随机的“山丘型”虚警目标,两者距离差与双频干扰频差有关。双频干扰中两分量互相压制,即当任一干扰分量强度恒定时,随着另一个分量的增强,前者形成的虚警目标电平缓慢下降,最终降速基本恒定,而后者形成虚警目标电平逐渐升高,直至电平恒定;若双频干扰信号两分量同比例增强,则两个虚警目标电平均在初期近似线性上升,而后增速逐渐降低至零。     

电磁发射用脉冲电抗器应力分析及结构设计

基于对电磁力以及热应力的解析计算公式的推导,运用ANSYS有限元仿真软件对固定电抗器顶底端面情况下的铜箔进行电磁-温度-结构耦合分析,分别得出热应力及所受总应力与应变的分布情况。进一步对电抗器的结构进行优化,综合考虑其结构强度要求与连发温度要求,确定电抗器的最优设计结构,最终通过试验验证出仿真与设计方案真实可信。     

Optimal control policies for an inventory system with commitment lead time

We consider a firm which faces a Poisson customer demand and uses a base‐stock policy to replenish its inventories from an outside supplier with a fixed lead time. The firm can use a preorder strategy which allows the customers to place their orders before their actual need. The time from a customer's order until the date a product is actually needed is called commitment lead time. The firm pays a commitment cost which is strictly increasing and convex in the length of the commitment lead time. For such a system, we prove the optimality of bang‐bang and all‐or‐nothing policies for the commitment lead time and the base‐stock policy, respectively. We study the case where the commitment cost is linear in the length of the commitment lead time in detail. We show that there exists a unit commitment cost threshold which dictates the optimality of either a buy‐to‐order (BTO) or a buy‐to‐stock strategy. The unit commitment cost threshold is increasing in the unit holding and backordering costs and decreasing in the mean lead time demand. We determine the conditions on the unit commitment cost for profitability of the BTO strategy and study the case with a compound Poisson customer demand.     

利用径向力平衡飞行控制的航天器高精度轨道捕获方法

为实现对探测器轨道形状与高度的精准调整,提出一种径向力平衡飞行的航天器连续推力控制新方法。建立连续推力平衡飞行的动力学极坐标模型,并推导出特殊条件下的解析轨道解,进一步分析边值条件,给出连续推力的控制律。利用这一平衡飞行控制理论,构建轨道捕获的最优控制策略。考虑推力器的推力水平,通过一次或多次的控制过程,实现对轨道形状、轨道高度及轨道相位的综合调整。数值仿真表明:利用平衡飞行的轨道控制方法,配置微小推力器的空间引力波探测器可以实现高精度的轨道捕获;该方法具有控制过程可解析、计算量小、简便、实用等特点。     

传递矩阵法在连续系统中的作用

在分析离散系统振动时,传递矩阵法是一种重要的方法。将传递矩阵法应用到具有分布质量的连续系统中,给出了具有Rayleigh阻尼形式的梁在随机激励作用下响应分析。     

Contracts and coordination: Supply chains with uncertain demand and supply

Considering a supply chain with a supplier subject to yield uncertainty selling to a retailer facing stochastic demand, we find that commonly studied classical coordination contracts fail to coordinate both the supplier's production and the retailer's procurement decisions and achieve efficient performance. First, we study the vendor managed inventory (VMI) partnership. We find that a consignment VMI partnership coupled with a production cost subsidy achieves perfect coordination and a win‐win outcome; it is simple to implement and arbitrarily allocates total channel profit. The production cost subsidy optimally chosen through Nash bargaining analysis depends on the bargaining power of the supplier and the retailer. Further, motivated by the practice that sometimes the retailer and the supplier can arrange a “late order,” we also analyze the behavior of an advance‐purchase discount (APD) contract. We find that an APD with a revenue sharing contract can efficiently coordinate the supply chain as well as achieve flexible profit allocation. Finally, we explore which coordination contract works better for the supplier vs. the retailer. It is interesting to observe that Nash bargaining solutions for the two coordination contracts are equivalent. We further provide recommendations on the applications of these contracts. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 305–319, 2016     

一种改进的连续域蚁群算法

简要介绍了蚁群算法,并从解决连续域问题的角度分析了段海滨等提出的基于网格划分策略的连续域蚁群算法的基本原理,针对该算法的特点和存在的缺陷,提出了改进的办法:在前期用遗传算法快速生成初始信息素,再利用蚁群算法寻求精确解。最后通过对一个二维连续域函数优化仿真实验,证明了改进后蚁群算法的有效性。仿真实验结果证明:改进后的蚁群算法无论是时间性能还是优化性能都明显优于改进前的蚁群算法,克服了蚁群算法的缺陷,大大提高了算法的速度和求解效率,达到了时间性能和优化性能的双赢。     

Production to order and off‐line inspection when the production process is partially observable

This study combines inspection and lot‐sizing decisions. The issue is whether to INSPECT another unit or PRODUCE a new lot. A unit produced is either conforming or defective. Demand need to be satisfied in full, by conforming units only. The production process may switch from a “good” state to a “bad” state, at constant rate. The proportion of conforming units in the good state is higher than in the bad state. The true state is unobservable and can only be inferred from the quality of units inspected. We thus update, after each inspection, the probability that the unit, next candidate for inspection, was produced while the production process was in the good state. That “good‐state‐probability” is the basis for our decision to INSPECT or PRODUCE. We prove that the optimal policy has a simple form: INSPECT only if the good‐state‐probability exceeds a control limit. We provide a methodology to calculate the optimal lot size and the expected costs associated with INSPECT and PRODUCE. Surprisingly, we find that the control limit, as a function of the demand (and other problem parameters) is not necessarily monotone. Also, counter to intuition, it is possible that the optimal action is PRODUCE, after revealing a conforming unit. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

An adaptive forecasting algorithm and inventory policy for products with short life cycles

Products with short life cycles are becoming increasingly common in many industries, such as the personal computer (PC) and mobile phone industries. Traditional forecasting methods and inventory policies can be inappropriate for forecasting demand and managing inventory for a product with a short life cycle because they usually do not take into account the characteristics of the product life cycle. This can result in inaccurate forecasts, high inventory cost, and low service levels. Besides, many forecasting methods require a significant demand history, which is available only after the product has been sold for some time. In this paper, we present an adaptive forecasting algorithm with two characteristics. First, it uses structural knowledge on the product life cycle to model the demand. Second, it combines knowledge on the demand that is available prior to the launch of the product with actual demand data that become available after the introduction of the product to generate and update demand forecasts. Based on the forecasting algorithm, we develop an optimal inventory policy. Since the optimal inventory policy is computationally expensive, we propose three heuristics and show in a numerical study that one of the heuristics generates near‐optimal solutions. The evaluation of our approach is based on demand data from a leading PC manufacturer in the United States, where the forecasting algorithm has been implemented. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.