基于时滞分割法的具有leakage项时滞的离散型神经网络状态估计

摘要：研究一类具有leakage时滞的离散型神经网络的状态估计问题．通过构造新的Lyapunov泛函得到保证估计误差全局渐近稳定的充分条件,并通过求解一个线性矩阵不等式（LMI）得到状态估计器的增益矩阵．采用一种新的时滞分割方法将变时滞区间分割为多个子区间,使该结果在获得更小的保守性同时也降低了计算的复杂度．     

预定相遇态势的潜射鱼雷射击及其技术方法

为发挥鱼雷的作战效能,提出潜射鱼雷有利相遇态势的概念,指出当一次转角射击不能满足鱼雷以有利相遇态势接近并发现目标时,各种自导方式的鱼雷均需要二次转角射击。在给出二次转角射击时机、解算模型的基础上,着重对预定相遇态势射击的关键----二次转向点的选择问题进行了系统研究,引入基于鱼雷自导探测距离的二次转向点与预定相遇点之间距离的选择方法,使得二次转向点的选择更具合理性和针对性,且适用于包括直航鱼雷在内的各种鱼雷。     

基于ARMA辨识的色噪系统状态参数鲁棒估计

实际环境中观测系统的噪声,同时存在着白噪、色噪声和尖点噪声的影响.已有的研究都仅考虑白噪或色噪声,首次将实际系统中可能出现的所有噪声纳入观测方程,推导出统一的带白噪形式的观测方程.新观测方程在色噪声ARMA辨识基础上,可以直接用于传统的卡尔曼滤波算法,避免了扩维滤波.于是状态参数的稳健估计归结为ARMA参数的辨识.重点研究了自由参数选取与输入噪声之间的关系,将鲁棒支持向量回归机的优化问题转换成最大后验估计问题,为合理选择自由参数提供了理论依据.仿真结果验证了新算法的有效性.     

四阶累积量的MIMO雷达角度估计算法

针对色噪声环境下的MIMO雷达目标角度估计问题,提出一种新的参数估计算法.通过计算MIMO雷达接收数据的四阶累积量,并对构造出的累积量矩阵进行特征分解,结合MUSIC算法和ESPRIT算法实现了雷达目标的角度估计.在保证阵元扩展能力和目标分辨力的基础上进行了低复杂度改进,去掉了冗余信息,实现了目标参数的有效估计;同时由于采用四阶累积量,提高了算法抑制高斯噪声的能力,更利于工程应用.最后计算机仿真结果证实了算法的有效性和可行性.     

色噪声环境下MIMO雷达相干目标角度估计算法

针对色噪声环境下的MIMO雷达相干目标角度估计问题,提出一种基于目标信息矢量重构的角度估计算法.算法对MIMO雷达的接收数据进行了低复杂度改进,通过计算四阶累积量,得到一组矢量并证明该矢量包含所有目标的角度信息,通过重构Toeplitz矩阵,结合MUSIC算法实现了色噪声环境下MIMO雷达相干目标的角度估计.算法保留了MIMO雷达的阵元扩展能力和目标分辨力,具有自动抑制加性高斯白噪声和色噪声的能力,实现了相干目标的有效估计,更利于在实际中应用.最后计算机仿真结果证实了算法的有效性和可行性.     

抑制成像数据噪声的模糊多目标算法

以模糊数学和决策理论为基础,通过建立成像数据模糊指数函数及平方误差 模糊指数函数,提出了一种称为模糊多目标优化的新的算法模型,对成像数据的噪声进行抑 制实现数据优化。实验结果表明,所提出的模糊多目标优化算法模型有较强的抑制噪声能 力,理论和实验有较好的一致性。     

Integrating decisions with advance supply information in an assemble-to-order system

We study a periodic-review assemble-to-order (ATO) system with multiple components and multiple products, in which the inventory replenishment for each component follows an independent base-stock policy and stochastic product demands are satisfied according to a First-Come-First-Served rule. We assume that the replenishment for various component suffers from lead time uncertainty. However, the decision maker has the so-called advance supply information (ASI) associated with the lead times and thus can take advantage of the information for system optimization. We propose a multistage stochastic integer program that incorporates ASI to address the joint optimization of inventory replenishment and component allocation. The optimal base-stock policy for the inventory replenishment is determined using the sample average approximation algorithm. Also, we provide a modified order-based component allocation (MOBCA) heuristic for the component allocation. We additionally consider a special case of the variable lead times where the resulting two-stage stochastic programming model can be characterized as a single-scenario case of the proposed multistage model. We carry out extensive computational studies to quantify the benefits of integrating ASI into joint optimization and to explore the possibility of employing the two-stage model as a relatively efficient approximation scheme for the multistage model.     

Application of Markov renewal theory and semi-Markov decision processes in maintenance modeling and optimization of multi-unit systems

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.     

Optimal allocation of minimal repairs in parallel and series systems

In reliability engineering, the concept of minimal repair describes that the repair brings the failed unit (eg, system or component) to the situation which is same as it was just before the failure. With the help of the well‐known Gamma‐Poisson relationship, this paper investigates optimal allocation strategies of minimal repairs for parallel and series systems through implementing stochastic comparisons of various allocation policies in terms of the hazard rate, the reversed hazard rate, and the likelihood ratio orderings. Numerical examples are presented to illustrate these findings as well. These results not only strengthen and generalize some known ones in the seminal work of Shaked and Shanthikumar, but also solve the open problems proposed by Chahkandi et al.'s study and Arriaza et al.'s study.     

非均匀湍流场中螺旋桨噪声研究

针对螺旋桨在湍流中的非定常噪声问题,在均匀湍流下螺旋桨宽频噪声相关性法的基础上,推导了非均匀湍流下螺旋桨宽频噪声的公式。在均匀湍流的研究中使用了十桨叶螺旋桨模型,并将计算结果与试验数据进行了对比,发现吻合较好。对于非均匀湍流中的问题,研究发现湍流的不均匀程度不会对宽频谱波峰的位置产生影响,噪声谱波峰的位置仍然取决于叶频,湍流的不均匀程度只会改变叶频处的波峰高度。最后研究了均匀湍流和非均匀湍流中侧斜角对螺旋桨噪声的影响,发现桨叶侧斜角的存在会降低螺旋桨在湍流中受到的宽频噪声。