Performance of real-time distributed arrival time control in heterarchical manufacturing systems

A highly distributed feedback control algorithm for autonomous part entities in heterarchical manufacturing systems is presented in this paper. A difference equation-based model is developed to analyze the discrete time dynamics of the resulting nonlinear control system. Control parameters are found analytically that guarantee that the system is bounded under disturbances. The dynamic response to: (i) changes in due dates; and (ii) the bulk arrival of parts is presented. The ability of the system to exponentially reduce the mean and variance of due-date deviation in the single machine case makes it an attractive option for real-time control of just-in-time production.     

Optimal inspection of a finite population

This article presents a method for determining an optimal quality control (QC) inspection frequency for a manufacturing process where a specified number of items will be produced and where, if the process goes out of control and generates a defective item, it stays out of control. In addition, there is a QC inspection procedure than can detect a defective item. The frequency of inspection is based on minimizing the total cost. The total cost includes the cost of QC inspections plus the cost of manufacturing defective items. In this application the cost of manufacturing defective items is, after identifying a defective item, the cost of checking previously manufactured items until it is determined when the process went out of control, i.e., until a good item is found.     

Optimal control with responses and control force constraints

Abstract

In order to assure safety and serviceability, structural responses are kept within certain limits by active control methods. Control forces as well as responses (displacement and velocity) are considered constraints in an optimal control system. The exact solution of the optimal control system under the aforementioned constraints is derived in the first part of the paper. An approximate solution is also suggested in the paper. An example dealing with a six‐story building is presented in the last part of the paper to demonstrate the application of the approximate approach.     

Optimal control of sprinklers in compartment fires

There is no doubt that increased application of sprinkler protection through a building can significantly reduce fire losses. In many compartment fires, the water damage is far more extensive than the flame damage. This paper examines the possibility of controlling the flow of water from sprinklers in an optimal way so as to minimize the water damage and the overall property damage. Two cases are considered. The first when the water damage is proportional to the total amount of water and the second when it is proportional to the integral of the square of the water flow rate. © 1997 John Wiley & Sons, Ltd.     

基于自适应引力算法的桥梁监测传感器优化布置

针对桥梁健康监测中传感器布置优化问题,提出了一种基于自适应引力算法的传感器优化布置方法。以模态置信准则为基础,构造满足传感器优化布置的适应度函数;针对引力搜索算法开发能力不足,对衰减因子α进行了自适应改进。搜索初期α较小,粒子以较大步长进行全局搜索,增强了算法的搜索效率;搜索后期α较大,粒子以较小的步长进行局部搜索,提高了算法的搜索能力,避免落入局部极值点。改进后的自适应引力算法通过双重编码的方式,使算法可以解决离散型的传感器布置问题;以马水河大桥为例,验证算法的可行性。结果表明,改进后的算法有很好的寻优能力,能够准确高效的确定传感器优化位置。     

Distributed policy search reinforcement learning for job-shop scheduling tasks

We interpret job-shop scheduling problems as sequential decision problems that are handled by independent learning agents. These agents act completely decoupled from one another and employ probabilistic dispatching policies for which we propose a compact representation using a small set of real-valued parameters. During ongoing learning, the agents adapt these parameters using policy gradient reinforcement learning, with the aim of improving the performance of the joint policy measured in terms of a standard scheduling objective function. Moreover, we suggest a lightweight communication mechanism that enhances the agents' capabilities beyond purely reactive job dispatching. We evaluate the effectiveness of our learning approach using various deterministic as well as stochastic job-shop scheduling benchmark problems, demonstrating that the utilisation of policy gradient methods can be effective and beneficial for scheduling problems.     

基于分布式控制的即插即用机械臂系统

提出了将即插即用技术与嵌入分布式控制系统应用于小型通用机械臂系统的方法,详细介绍了基于此方法研制的Rinar机械臂系统。该机械臂由个人计算机(PC)通过通用串口总线(USB)接口控制,支持热插拔,内部采用PID算法进行运动控制。实验显示,Rinar能快速响应用户指令,运动性能良好,证明了通过USB接口与嵌入式分布式控制机构对机械臂进行控制的可行性和有效性。     

Optimal control of photoelectron emission by realistic waveforms

Recent experimental techniques in multicolor waveform synthesis allow the temporal shaping of strong femtosecond laser pulses with applications in the control of quantum mechanical processes in atoms, molecules, and nanostructures. Prediction of the shapes of the optimal waveforms can be done computationally using quantum optimal control theory. In this work we demonstrate the control of above-threshold photoemission of one-dimensional hydrogen model with pulses feasible for experimental waveform synthesis. By mixing different spectral channels and thus lowering the intensity requirements for individual channels, the resulting optimal pulses can extend the cutoff energies by at least up to 50% and bring up the electron yield by several orders of magnitude. Insights into the electron dynamics for optimized photoelectron emission are obtained with a semiclassical two-step model.     

自适应网格方法在Stokes问题形状最优控制中的应用

为了求解流体力学中的形状最优控制问题,本文提出了一种与最优化准则方法相耦合的自适应网格方法.优化的目标是使得流体流动的能量耗散达到最小,状态方程是Stokes问题.本算法可以在减少计算量的情况下,保证流体的界面达到较高的分辨率.最优化算法采用的是非常稳定的经典最优化准则方法,自适应网格的指示函数是通过材料分布的信息得到的.虽然本文只是考虑了Stokes问题,但所得算法可以用来解决很广泛的一类流体动力学中的形状或拓扑最优化问题.     

一类离散非线性系统迭代最优学习控制

就一类离散非线性系统的迭代学习控制 ,提出了最优迭代因果学习律的存在性条件 .如果迭代初态严格重复 ,则迭代输出收敛于期望输出 .该结论直接推广了线性离散系统最优迭代学习相关结果     

Scheduling distributed flowshops with flexible assembly and set-up time to minimise makespan

The scheduling problems under distributed production or flexible assembly settings have achieved increasing attention in recent years. This paper considers scheduling the integration of these two environments and proposes an original distributed flowshop scheduling problem with flexible assembly and set-up time. Distributed production stage is deployed several homogeneous flowshop factories that process the jobs to be assembled into final products in the flexible assembly stage. The objective is to find a schedule, including a production subschedule for jobs and an assembly subschedule for products, to minimise the makespan. Such a scheduling problem involves four successive decisions: assigning jobs to production factories, sequencing jobs at every factory, designating an assembly machine for each product and sequencing products on each assembly machine. The computational model is first established, and then a constructive heuristic (TPHS) and two hybrid metaheuristics (HVNS and HPSO) are proposed. Numerical experiments have been carried out and results validate the algorithmic feasibility and effectiveness. TPHS can obtain reasonable solutions in a shorter time, while metaheuristics can report better solutions using more yet acceptable time. HPSO is statistically comparable yet less robust compared with HVNS for small-scale instances. For the large-scale case, HPSO outperforms HVNS on both effectiveness and robustness.     

基于分布式控制的自重构机器人变形策略

设计了一种形状类似立方体、运动空间为三维的称为M-Cubes的新型自重构模块机器人.提出了建立在路径规划和连接规划基础上的变形运动策略,此方法有效地解决了模块在自重构过程中计算量大的棘手问题,优化了系统在变形过程中的运动路径.最后利用Java 3D对模块的本地连接规则进行了仿真,验证了该变形方法的可行性和有效性.     

Optimal control of an induction heating process using automatic differentiation

We consider an optimal control problem arising in an induction heating process. The main difficulty is to obtain accurate and efficient derivatives of the discrete form of the cost function. In this work we use automatic differentiation. Unlike numerical differentiation based on finite differences, derivatives generated by automatic differentiation are free of truncation error. Numerical results show the performance of the method in terms of accuracy and computational efficiency. Copyright © 2005 John Wiley & Sons, Ltd.     

压水型核反应堆功率控制系统的优化设计

在分析了压水型反应堆功率控制系统的前提下，针对其特殊的控制要求，运用基于输出反馈的次最优控制的设计方法和Matlab中的NCD模块，最终实现了系统的优化设计，并对系统进行了某一功率水平下的仿真试验和其它工况下的鲁棒性试验．结果表明。改进后的系统性能有了较大改善。     

Optimal age-based inspection scheme for condition-based maintenance using A* search algorithm

In condition-based maintenance (CBM) with periodic inspection, the system is preventively replaced if failure risk, which is calculated based on the information obtained from inspection, exceeds a pre-determined threshold. The determination of optimal replacement threshold is often based on the minimisation of average maintenance costs per unit time due to preventive and failure replacements over a long time horizon. It is often assumed that inspections are performed at equal time intervals with no cost. However, in practice, inspections require labour, specific test devices, and sometimes suspension of operations and, thus, it is reasonable to inspect less frequently during the time the system is in its early age and/or in a healthier state and to perform inspections more frequently as time passes and/or as the system degrades. In other words, an age-based inspection scheme.

This paper proposes a novel two-phase approach for the determination of an optimal replacement threshold and an optimal age-based inspection scheme for CBM such that the total long-run average costs of replacements and inspections are minimised. First, it takes into account failure and preventive replacement costs to determine the optimal replacement threshold assuming that inspections are performed at equal time intervals with no cost. This assumption is, subsequently, relaxed and its consequences on total average cost are evaluated using a proposed iterative procedure based on A* search algorithm to obtain the optimal age-based inspection scheme. The proposed approach is illustrated through a numerical example.     

Detection of an appropriate pharmaceutical company to get a suitable vaccine against COVID-19 with minimum cost under the quality control process

Some international pharmaceutical companies have succeeded in producing vaccines against COVID-19. Countries all over the world have aimed to obtain these vaccines with minimum cost. We consider a set of K-independent Markovian waiting lists. Each list contains a set of countries, where each one of them has an exponential service time and a Poisson arrival process. These companies differ in some characteristics such as the vaccine production cost and the speed of the required quantity delivery. We present a new detection model that helps in providing an appropriate decision to choose a suitable company. Moreover, the concept of balking and the retention of reneged countries is taken into consideration under the quality control process of each waiting list. Under steady state, we face an interesting and difficult discrete stochastic optimization problem. Its solution gives an optimal distribution of the searching effort, which is bounded by a known probability distribution. A simulation study has been derived to get the minimum value of the paid cost random values. The highest service rate, the total expected profit of each queuing system, and the optimum performance measures, which depend on this cost, have been obtained to show the effectiveness of this model.     

分布参数结构控制中溢出抑制的并行滤波法

提出了并行滤波控制方法抑制分布参数结构主动控制中的溢出。对无穷维分布参数结构,依据有限维降阶模型设计控制器会导致系统闭环性能变差,并有可能使系统失稳。文中针对分布参数结构特性设计了滤波增广结构,对增广系统设计带观测器的状态反馈构成控制器。在给出该方法原理的基础上,提出了并行滤波控制针对被控结构摄动的鲁棒稳定界。仿真算例表明,此方法在保证受控模态控制效果的同时有效地抑制了溢出。     

Numerical approximation of optimal control for distributed diffusion Hopfield neural networks

This work presents a numerical approximation of optimal control problems for non‐linear distributed Hopfield Neural Network equations with diffusion term. For one spatial dimensional case, a semi‐discrete numerical algorithm was constructed to find optimal control variable using finite element discretization, updated conjecture gradient iteration method. Furthermore, experiments demonstration will be implemented to show the effectiveness and stability through 3D graphics simulations. Copyright © 2006 John Wiley & Sons, Ltd.     

结构噪声主动控制在时域声辐射模态下的仿真研究

以简支矩形板为例，提出了利用时域声辐射模态进行声辐射研究。研究表明时域声辐射模态既与时间无关，且互相独立，使得计算和控制声功率得以简化。针对瞬时声功率主要由第一阶辐射模态的声功率所决定的特点，在时域里进行结构噪声的主动控制研究，通过抵消第一阶辐射模态的声功率使得总的声功率得以有效降低。在此基础上，建立了时域声辐射模态的状态空间方程，对该方程的性能进行了分析，并利用最优控制算法的自适应反馈控制系统进行仿真计算。最后讨论了不同情况下的计算精度，并对影响仿真结果的因素进行了分析。     

Optimal cost design of water distribution networks using harmony search

This study presents a cost minimization model for the design of water distribution networks. The model uses a recently developed harmony search optimization algorithm while satisfying all the design constraints. The harmony search algorithm mimics a jazz improvisation process in order to find better design solutions, in this case pipe diameters in a water distribution network. The model also interfaces with a popular hydraulic simulator, EPANET, to check the hydraulic constraints. If the design solution vector violates the hydraulic constraints, the amount of violation is considered in the cost function as a penalty. The model was applied to five water distribution networks, and obtained designs that were either the same or cost 0.28–10.26% less than those of competitive meta-heuristic algorithms, such as the genetic algorithm, simulated annealing and tabu search under similar or less favorable conditions. The results show that the harmony search-based model is suitable for water network design.