灰度图像二维最小类方差递推及差分演化的快速分割

为克服Otsu法阈值偏离及一维最小类方差法在含噪图像分割中性能不佳的问题,基于图像灰度级二维直方图,提出一种二维最小类方差快速阈值化方法.通过递推方式计算得到图像前景及背景在不同阈值向量上的灰度级类概率及类均值,在此基础上,应用差分演化算法搜寻使图像类方差最小的阈值向量,并用该阈值向量对图像实施分割.在合成及真实图像上的实验结果表明,采用文中方法可获得良好的分割性能,有效地克服了Otsu法及一维最小类方差法的不足;采用递推及差分演化算法使计算时间大幅降低,可满足工程应用需求.     

预防阈值控制策略及其实现

对机器故障为一般概率分布的不可靠制造系统,提出一种预防阈值控制策略和实现 这一控制策略的参数优化方法.应用扰动分析法得到性能指标对控制参数的灵敏度估计,并 证明了估计的无偏性,又利用随机逼近技术优化控制参数.仿真结果验证了控制策略的有效 性.     

不完全柔性制造系统的最优控制

考虑具有随机需求的不完全柔性制造系统的最优控制，系统在各种产品间的切换时间是不可忽略的。运用马尔可夫最优决策过程归纳方法，导出机器服务率的最优控制策略。通过分析最优值函数的性质，证明最优策略具有简单的阈值结构，从而可得到次优生产策略--阈值控制策略。     

基于中心扰动的区间值模糊集图像阈值分割算法

针对基于区间值模糊集的图像阈值分割问题,提出了一种基于中心扰动的区间值模糊集图像阈值分割算法.采用对目标及背景中心进行扰动的方式,考虑不确定、不精确信息对图像类别中心的影响,并利用限制等价函数构建图像的区间值模糊集模型;在提出一种区间值模糊集上区别度量的基础上建立目标函数来搜索最佳分割阈值.通过对三种类型的图像数据进行仿真实验,结果表明提出的方法在视觉和指标上总体得到了较好的结果,证明了该算法的有效性.     

一种自适应模糊阈值区间的图像分割方法

针对图像分割边缘不准确的问题,研究了一种基于模糊理论的阈值区间的图像分割方法.在首先介绍的模糊阈值分割的基本原理上,提出了一种分层分割图像的思想.根据图像具有模糊的性质,利用模糊阈值法得到一个图像分割的调和阈值,再将每一层根据像素统计直方图信息得到一个本层次的阈值区域,最后用模糊阈值法得到的阈值调和阈值区域,使最终的分割阈值区间更精确.最后,根据相邻层相连背景像素相似的原则,逐层分割图像.实验结果表明该方法具有较好的分割效果.     

基于新阈值函数的小波去噪方法

小波阈值去噪是信号处理中一种重要的去噪方法,针对常用硬阈函数不连续的特点以及软阈值函数存在偏差的问题,提出了一种新的阈值处理方法,在matlab7．0中的仿真试验结果表明,新的阈值方法的去噪效果无论在视觉效果上,还是在信噪比和最小均方误差意义上均优于传统的硬阈值和软阈值。     

基于小波分析的自适应阀值改进算法

针对小波边缘检测阈值设定问题.本文提出了一种基于小波分析的改进阈值设定方法,采用一个矫正因子β来构造一个新的阈值函数,调整软硬阈值的恒定偏差.实验证明新阈值函数不但整体上连续性好而且在在克服硬阈值函数的不连续和软阈值函数在处理较大小波系数时总存在恒定偏差这两个不足的同时,又保留了软、硬阈值函数原有的优点.     

一种带有重心调节机构的作业型飞行机器人建模与控制

针对作业型飞行机器人完成抓取、搬运等任务时所产生的重心偏移问题,设计了一种带有重心调节机构的作业型飞行机器人,并提出了一种重心调节控制策略.该方法通过对作业装置中的机械臂进行运动学推导,动态计算出机械臂运动时复合系统重心位置的改变量,利用力矩平衡方程计算得到调节机构所需转动的角度,从而实现对复合系统重心的调节.为验证所提出控制策略的有效性,在Matlab仿真环境中,分别研究了有无重心调节控制时机械臂运动对复合系统重心轨迹和定点悬停位姿的影响.通过户外实物实验测试了飞行机器人搭载负载情况下,调节机构在定点悬停作业时的稳定效果.实验结果表明,在所述控制策略下,重心调节机构能够在飞行机器人作业过程中实时调节复合系统重心的偏移量,验证了控制策略的有效性.     

制造系统的递阶滚动优化调度模型

研究的对象是只有一台不可靠（failure-prone)机器的非完全柔性制造系统，该系统能生产多种产品，但在同一时刻只能生产一种产品，并且当机器由生产一种产品向生产另一种产品切换时，需要考虑setup时间及其成本，待决策变量是setup序列及产品生产率，本文基于非完全柔性制造系统的特点，引入递阶层控的思想，采用新的递阶结构框架和阈值控制策略，对问题进行分解，建立了考虑setup时间及成本的递阶流率控制最优化调度模型，并给出了递阶的滚动优化算法，仿真结果表明，这种调度策略更易于工程实现。     

基于Backstepping 的非仿射非线性系统鲁棒控制

针对一类不确定非仿射非线性系统的跟踪控制问题, 提出一种鲁棒Backstepping 控制策略. 首先, 为利用仿 射非线性方法设计控制器, 给出一种适用于全局的非仿射非线性近似方法; 然后, 设计快速收敛非线性微分器以估计复合干扰和获取虚拟信号的微分, 进而给出不确定非仿射非线性系统的复合控制器, 其中鲁棒项和阻尼项分别用于减少逼近误差和近似方法中动态误差对系统跟踪的影响; 最后, 通过仿真实验验证了所提出方法的有效性.     

A simulation optimization approach in production planning of failure prone manufacturing systems

In this paper, the implementation of a new method to control the production rate of manufacturing systems, based on the combination of stochastic optimal control theory, discrete event simulation, experimental design and response surface methodology is outlined. The system under study consists of several parallel machines, multiple-product manufacturing system. Machines are subject to failures and repairs and their capacity process is assumed to be a finite state Markov chain throughout the analytical control model. The problem is to choose the production rates so as to minimize the expected discounted cost of inventory/backlog over an infinite horizon. We first show that, for constant demand rates and exponential failure and repair times distributions of the machines, the hedging point policy is optimal. The structure of the hedging point policy is then parameterized by factors representing the thresholds of involved products. With such a policy, simulation experiments are combined to experimental design and response surface methodology to estimate the optimal control policy. We obtain that the hedging point policy is also applicable to a wide variety of complex problems including non-exponential failure and repair times distributions and random demand rates. Analytical solutions may not be easily obtained for such complex situations.     

A simulation optimization based control policy for failure prone one-machine,two-product manufacturing systems

This paper presents the optimal flow control for a one-machine, two-product manufacturing system subject to random failures and repairs. The machine capacity process is assumed to be a finite state Markov chain. The problem is to choose the production rates so as to minimize the expected discounted cost of inventory/backlog over an infinite horizon. We first show that for constant demand rates and exponential failure and repair time distributions of the machine, the hedging point policy is optimal. Next, the hedging point policy is extended to non-exponential failure and repair time distributions models. The structure of the hedging point policy is parameterized by two factors representing the thresholds of involved products. With such a policy, simulation experiments are coupled with experimental design and response surface methodology to estimate the optimal control policy. Our results reveal that the hedging point policy is also applicable to a wide variety of complex problems (i.e. non-exponential failure and repair time distributions) where analytical solutions may not be easily obtained.     

Scheduling and control of failure prone systems with demand uncertainty and job overlaps

Given that the overlapping of jobs is permitted, the paper studies the scheduling and control of failure prone production systems,i, e.so-called settings with demand uncertainty and job overlaps. Because a variable demand resource is revolved in the production and corrective maintenance control problems of the system, which switched randomly between zero and a maximum level, it is difficult to obtain the analytical solutions of the optimal single hedging point policy. An asymptotic optimal scheduling policy is presented and a double hedging point policy is offered to control simultaneously the production rate and the corrective maintenance rate of the system. The corresponding analytical solutions and approximate solutions are obtained. Considering the relationship of production, corrective maintenance and demand variable, an approximate optimal single hedging point control policy is proposed. Numerical results are presented.     

Optimality of hedging point policies in the production control offailure prone manufacturing systems

We study the necessary and sufficient conditions for the optimality of the hedging point policy for production systems in which the failure rate of machines depends on the rate of production. We focus on a one machine one part-type and infinite horizon discounted cost problem. It is shown that when the failure rate is independent of the rate of production and a constant, the hedging point policy is provably optimal. The main result of this paper is to show that the linearity of the failure rate function is both necessary and sufficient for the optimality of the hedging point policy     

Pade approximants for the transient optimization of hedging controlpolicies in manufacturing

Part production is considered over a finite horizon in a single-part multiple-failure mode manufacturing system. When the rate of demand for parts is constant, for Markovian machine-mode dynamics and for convex running cost functions associated with part inventories or backlogs, it is known that optimal part-production policies are of the so-called hedging type. For the infinite-horizon case, such policies are characterized by a set of constant critical machine-mode dependent inventory levels that must be aimed at and maintained whenever possible. For the finite-horizon (transient) case, the critical levels still exist, but they are now time-varying and in general very difficult to characterize. Thus, in an attempt to render the problem tractable, transient production optimization is sought within the (suboptimal) class of time-invariant hedging control policies, a renewal equation is developed for the cost functional over finite horizon under an arbitrary time-invariant hedging control policy     

Stohastic optimal production control problem with corrective maintenance

We consider a production control problem in a manufacturing system with failure-prone machines and a constant demand rate. The objective is to minimise a discounted inventory holding and backlog cost over an infinite planning horizon. The availability of the machines is improved through a corrective maintenance strategy. The decision variables are the production and the machine repair rates, which influence the inventory levels and the system capacity, respectively. It is shown that, for constant demand rates and exponential failure and repair times distributions of the machines, the hedging point policy is optimal. Such a policy is modified herein and parameterised by factors representing the thresholds of involved products and switching inventory levels for corrective maintenance. With the obtained policy, simulation experiments are combined to experimental design and response surface methodology to estimate the optimal production and corrective maintenance policies, respectively. The usefulness of the proposed approach is illustrated through a numerical example.     

On the ordering of optimal hedging points in a class ofmanufacturing flow control models

The optimal flow control policy of a single-product unreliable manufacturing system that must meet a constant demand rate is known to be a threshold type policy: safety production surplus levels called hedging points (thresholds) are associated with each discrete stochastic capacity state of the system and serve to protect the production process from uncertainty in future capacity availability. This correspondence extends and generalizes previous results on the ordering of optimal hedging points. The authors' method is based on examining special properties of the Bellman optimality conditions of the underlying stochastic control problem     

Optimal hedging point control for a failure-prone manufacturing system

This paper considers a manufacturing system with multiple operational modes producing one part type. The part processing time at each operational mode is exponentially distributed and its rate is controllable. The demand arrival is random and described by a Poisson process. By minimizing an infinite-horizon discounted expected cost function, the optimal service rate control is derived. It is proved that the optimal policy is of a hedging point structure by examining the properties of the optimal cost function such as convexity, monotonicity and asymptotic behaviours. The hedging points at different operational modes can be ordered according to their production capacities. The relationships of the hedging points with some system parameters are presented. These structural properties of the optimal control policy are helpful in finding simple and realistic suboptimal policies for practical manufacturing systems. A numerical example is given to demonstrate our results.     

The queueing equivalence to a manufacturing system with failures

The authors consider optimal production rate control in a failure prone manufacturing system. It is well known that the hedging point policy is the optimum controller for such a system. They show that under the hedging point policy the system can be treated as an M/M/1 queue. Therefore, existing results in queuing theory can be readily applied to obtaining the steady-state probability density function of the production surplus, based on which the optimal hedging point policy can be computed. To a large extent, the approach is based on sample path analysis. It not only provides an alternative way to solve the problem but also reveals some interesting insights