单片可编程数字信号处理器(DSP)在控制领域的应用趋势

分析了单片可编程数字信号处理器的特性,并着重同普通微处理器、微控制器作了结构及性能上的比较。介绍了现有的DSP 并预测了DSP 在控制领域中的应用趋势。     

惯导系统动基座对准精度评估方法

弹载惯性制导系统空中对准是机载战术导弹发射前必须完成的任务,其对准精度直接影响导弹系统的制导精度。利用最优平滑技术对弹载惯导系统传递对准效果进行评估,是分析导弹系统的战术性能和惯导系统自身器件性能的有效方法。Rauch-Tung-Striebel(1965)提出了固定区间平滑算法,Meditch(1967)提出了固定点平滑算法;Bierman(1983)、Watamabe(1989)等许多学者对RTS算法提出了改进方法,这些方法在保证平滑算法中数值的稳定性和提高计算效率方面有了明显改善。针对固定区间平滑算法所适应的对象,分析了这类平滑算法的特点,提出了RTS固定区间平滑算法的改进方法;结合弹载惯性制导系统传递对准效果评估,进一步证明了分析的正确性。     

U-D分解单步迭代滤波在飞行状态估计中的应用

针对单步迭代滤波常规算法数值鲁棒性差、滤波易于发散的缺点对误差协方差矩阵使用了 U - D分解 ,从而形成了一种基于 U - D分解的单步迭代滤波算法。该算法提高了数值鲁棒性 ,并且对相关的量测噪声有一定处理能力 ,应用于飞行状态的估计问题 ,获得了较为满意的结果     

Models for production planning under power interruptions

We present a robust optimization model for production planning under the assumption that electricity supply is subject to uncertain interruptions caused by participation in interruptible load contracts (ILCs). The objective is to minimize the cost of electricity used for production while providing a robust production plan which ensures demand satisfaction under all possible interruption scenarios. The combinatorial size of the set of interruption scenarios makes this a challenging problem. Furthermore, we assume that no probabilistic information is known about the supply uncertainty: we only use the information given in the ILC to identify an uncertainty set that captures the possible scenarios. We construct a general robust framework to handle this uncertainty and present a heuristic to compute a good feasible solution of the robust model. We provide computational experiments on a real‐world example and compare the performance of an exact solver applied to the robust model with that of the heuristic procedure. Finally, we include the operational impact of interruptions such as “recovery modes” in the definition of the uncertainty set. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Robust shortest path problems with two uncertain multiplicative cost coefficients

We consider a robust shortest path problem when the cost coefficient is the product of two uncertain factors. We first show that the robust problem can be solved in polynomial time by a dual‐variable enumeration with shortest path problems as subproblems. We also propose a path enumeration approach using a K ‐shortest paths finding algorithm that may be efficient in many real cases. An application in hazardous materials transportation is discussed, and the solution methods are illustrated by numerical examples. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

分布式放大前传中继辅助多用户对等通信中的鲁棒波束成形

针对分布式放大前传中继辅助多用户对等通信系统研究了存在非理想信道状态信息(CSI)时的分布式中继网络(DRN)鲁棒波束成形设计问题。采用统计CSI误差模型,考虑了两种鲁棒优化问题:一是从公平性的角度出发在DRN总发送功率约束下实现多个目的节点间的信干噪比(SINR)平衡;另一是从有效性的角度出发在保证各个目的节点服务质量需求(SINR大于预设门限)约束下最小化DRN总发送功率。对问题的分析和建模表明,在多用户情况下,这两个问题都是难以求解的优化问题。通过引入半定松弛(SDR)思想,将上述两种优化问题转化为可利用内点法有效求解的半定规划(SDP)问题。最后通过仿真验证了所提设计的鲁棒性能。     

一种基于灰色粒子滤波算法的机动AUV航深内测方法

本文提出了一种将灰色预测和小波变换与标准粒子滤波相结合的灰色粒子滤波算法（GPF）,并将其应用于机动AUV的航深内测。GPF针对机动AUV航深内测过程中由于AUV运动状态未知和测量噪声不断变化而导致的滤波失效问题,在粒子采样过程中结合了标准采样和灰色预测采样,保证了采样得到充分多的有效粒子。在计算粒子权重时,利用小波变换跟踪测量噪声统计特性的变化,提高了各粒子似然概率计算和权重分配的正确性。最后以外测法测得的高精度的机动AUV航深作为真实航深,对该GPF算法进行了实验对比验证,并与EKF和MMPF算法的结果作对比,实验结果表明了本文方法的有效性和实用性。     

基于迭代卡尔曼粒子滤波的目标跟踪算法研究

粒子滤波在基于图像序列的目标跟踪中获得了广泛应用．针对其计算量较大的问题,提出一种迭代卡尔曼粒子滤波算法,将非线性跟踪问题分解为线性子结构的全局状态空间模型和非线性子结构的局部状态空间模型,利用粒子滤波在卡尔曼滤波估计值的局部范围内搜索目标,逼近真实目标状态．将实验结果与粒子滤波进行比较,结果表明,迭代卡尔曼粒子滤波减少了粒子数,降低了计算量,能够对高机动目标进行实时稳定的跟踪．     

融合地理信息的粒子滤波被动跟踪算法

在粒子滤波机动目标跟踪中,为避免粒子集退化现象,通常采取大量的初始粒子数,因而带来了运算量大、跟踪精度低的问题.融合目标舰可能的航线及地理位置先验信息,将约束条件加入到粒子更新迭代中,对粒子的分布和权值进行调整.通过仿真对比加入约束前后算法的跟踪性能,可以看出融合地理信息后,较好地解决了粒子滤波计算量大的难题,提高了纯方位跟踪定位的精度.     

A robust queueing network analyzer based on indices of dispersion

We develop a robust queueing network analyzer algorithm to approximate the steady-state performance of a single-class open queueing network of single-server queues with Markovian routing. The algorithm allows nonrenewal external arrival processes, general service-time distributions and customer feedback. The algorithm is based on a decomposition approximation, where each flow is partially characterized by its rate and a continuous function that measures the stochastic variability over time. This function is a scaled version of the variance-time curve, called the index of dispersion for counts (IDC). The required IDC functions for the external arrival processes can be calculated from the model primitives or estimated from data. Approximations for the IDC functions of the internal flows are calculated by solving a set of linear equations. The theoretical basis is provided by heavy-traffic limits for the flows established in our previous papers. A robust queueing technique is used to generate approximations of the mean steady-state performance at each queue from the IDC of the total arrival flow and the service specification at that queue. The algorithm's effectiveness is supported by extensive simulation studies.