Dynamic dispatching for a flexible manufacturing system based on fuzzy logic

Variables in the production environment inevitably result in deviations from the generated schedules. These variables affecting the system performance should be considered when dealing with dynamic dispatching problems. In addition, determination of the dispatching rules based on a single performance criterion cannot satisfy the requirements of different production performances. In this research, a dynamic dispatching strategy for multiple performance measures based on fuzzy inference is proposed. First, the variables affecting the system performance are identified. Then, the fuzzy membership functions and the fuzzy inference rules are established based on the simulation data. According to the statuses of environment variables, the fuzzy inference is performed to find an appropriate dispatching rule at each decision point to meet the best multiple performance measures. An example of the application is presented. The simulation results indicate that the proposed fuzzy-based dynamic dispatching strategy has a very good and robust performance.     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

PID参数模糊自整定非线性系统仿真研究

针对常规PID控制器不能在线进行参数自整定的问题,构造了一个自适应模糊PID。通过模糊控制规则在线调整PID控制器的参数,并利用MATLAB语言对该控制器进行了计算机仿真。仿真研究表明,该控制器能迅速消除系统余差,改善普通模糊控制器的性能;既具有PID控制器高精度的优点,又具有模糊控制器快速、适应性能的特点,保证了调节系统具有良好的动、稳态特性。     

基于曲率加权累加的动态速度前瞻控制

针对在高速加工、快速检测等高速进给条件下,传统速度控制方法容易导致工件过切、机床抖动等问题,提出了基于离散衔接点曲率加权累加的速度前瞻程序段数动态选择的方法。首先,分析了基于5次样条曲线拟合离散衔接点方法,然后推导了到各衔接点的曲率表达式,最后根据各点曲率加权累加值进行动态速度前瞻程序段控制,并进行了仿真验证。仿真结果表明,动态速度前瞻避免了前瞻路径过短不能完成减速要求和前瞻段数过多占用系统资源,一定程度上解决了速度和精度的冲突问题,提高了系统的性能和加工效率。     

基于模糊PID控制的拉弯机控制系统的研究

针对一般控制方法对拉弯机难以达到预期的控制效果,提出了模糊自适应PID控制方法。用MATLAB仿真比较模糊自适应PID控制和常规PID控制效果,结果表明模糊自适应PID控制更能提高系统的动静态特性。     

航空遥感惯性稳定平台模糊/PID复合控制

为提高航空遥感惯性稳定平台控制系统稳定精度和扰动抑制能力,在常规PID控制的基础上设计了一种模糊控制与PID相结合的复合控制算法,分别应用于稳定平台横滚框及俯仰框系统进行实验验证。在三环控制系统位置环中将模糊控制与PID控制方法结合使用,并引入变论域思想,建立模糊/PID复合控制器,满足输出偏差变化不同时刻对PID参数整定的要求。通过模糊控制器实时调整PID参数,使系统具有良好的动、静态特性,实现多源扰动下惯性稳定平台的高稳定精度控制。分别通过仿真和静动态实验对方法进行分析和验证。实验结果表明:与常规PID控制及单纯模糊控制相比,模糊/PID复合控制器具有优越的扰动抑制能力和高稳定精度。相对传统PID控制,横滚框和俯仰框的静态均方根误差(RMS)值分别下降51%和73%、动态RMS值分别下降约20%和30%。     

航空蓄电池性能检测系统FUZZY控制器的设计

介绍一种用于航空蓄电池性能检测的FUZZY控制器的设计方案，分析了模糊控制规则和模糊控制表的设计方法。这种方法使得系统具有较高的稳态精度、良好的动态响应速度等优良特性。     

基于遗传算法的瓦楞纸生产原纸张力控制研究

针对瓦楞纸板生产过程中由于原纸张力控制系统具有时变性、负载扰动等难以实现参数整定的问题,提出了基于遗传算法优化的模糊PID控制方法,将遗传算法和模糊PID控制方法结合,用遗传算法来优化模糊控制规则和隶属度函数。实验结果表明:将该方法应用到原纸张力控制系统中,能使系统响应速度加快,抗干扰能力增强,具有良好的稳态精度和动态响应性能。     

一种模糊控制器在非最小相位系统中的应用

针对非最小相位系统具有右半平面零点，系统阶跃响应存在负调．以及常规方法控制不理想等问题，在分析常规模糊控制器的基础上设计了一种模糊积分控制器，改善了模糊控制器的动态和稳态性能。仿真结果证实了模糊积分控制器的可行性。     

交流伺服系统中PID参数模糊自整定控制器

为了改善以交流永磁同步电机为控制对象的伺服系统性能,在PID控制规律和模糊控制算法研究的基础上,提出了一种PID参数模糊自整定控制器。利用模糊推理方法建立了模糊控制规则,对交流伺服电机控制中的PID参数实现了自整定,并在Matlab中进行了仿真。仿真结果表明,该控制器改善了常规PID控制器的性能,使伺服系统具有良好的动、静态性能。     

Controlling flexible manufacturing systems based on a dynamic selection of the appropriate operational criteria and scheduling policy

This study presents the development of a multi-criteria control methodology for flexible manufacturing systems (FMSs). The control methodology is based on a two-tier decision making mechanism. The first tier is designed to select a dominant decision criterion and a relevant scheduling rule set using a rule-based algorithm. In the second tier, using a look-ahead multi-pass simulation, a scheduling rule that best advances the selected criterion is determined. The decision making mechanism was integrated with the shop floor control module that comprises a real-time simulation model at the top control level and RapidCIM methodology at the low equipment control level.A factorial experiment was designed to analyze and evaluate the two-tier decision making mechanism and the effects that the main design parameters have on the system’s performance. Next, the proposed control methodology was compared to a selected group of scheduling rules/policies using DEA. The results demonstrated the superiority of the suggested control methodology as well as its capacity to cope with a fast changing environment.     

带积分作用的模糊内模时滞控制器

将Smith预估器和内模控制结构结合起来，使用模糊控制器为主控制器，并用积分环节来消除系统所存在的稳态误差，理论分析可以证明，该结构就是内模控制器，无需滤波环节就可以得到良好的鲁棒性，而模糊控制器本身的非线性和鲁棒性也可以改善系统的动态性能和鲁棒性，经仿真研究发现，只要合理调整模糊比例因子和积分因子，该方法可以在一定的模型失配情况下得到比常规IMC更好的控制品质，且无稳态误差。     

热压成型装备精密温控研究

为了提高热压装备的温度控制精度,采用热电致冷器作为温度控制的主控元件构建了热压成型系统。针对热电致冷器呈现的复杂热电特性,在对其模型进行小信号线性化的基础上,获得了热电致冷器的控制模型。结合传统PID控制和模糊控制的优点,根据热电致冷器的非线性和可能的不确定性因素,建立PID参数自调整的推理规则,设计了热压成型装备温控的模糊PID控制器。阶跃响应实验表明该温控系统具有良好的动态性能和稳态品质,其升降温速度不小于1℃/s,温控精度可达0.2℃,满足热压成型装备精密温控的要求。     

模糊无模型自适应控制在CSTR中的仿真研究

连续搅拌反应釜(Continuously Stirred Tank Reactor,CSTR)是工业生产中常用的设备,其温度系统具有强非线性、耦合性、时变性的特点,反应机理复杂,精确建模困难,传统控制方法很难满足生产需要。为解决上述问题,采用基于数据驱动的无模型自适应方法(Model Free Adaptive Control,MFAC)对反应釜出料温度进行控制。在SIMULINK环境下搭建反应釜数学模型,采用基本MFAC方法对其进行仿真研究,针对控制器参数调整复杂的问题,采用模糊控制方法对无模型控制器参数进行优化。仿真实验结果表明,基于模糊控制的MFAC方法改善了系统动静态性能指标,系统的抗干扰能力和自适应能力得到增强。该方法对反应釜实际生产具有一定的指导作用。     

电液位置伺服系统的三维模糊PID控制

建立了阀控非对称液压缸的动力学模型，其推导过程可以用于任意电液位置伺服系统的数学建模；把模糊控制理论引入了伺服系统，设计了三维模糊PID控制器，基于Matlab／Stimulink软件平台进行了可视化仿真，改善了系统静动态性能和响应速度，为今后多输入一多输出问题的研究提供了可行的思路和方法。     

阀控非对称伺服缸基于粒子群优化的模糊PID控制器研究

针对阀控非对称伺服缸非线性、参数时变的特点,考虑到油液压缩特性的影响,建立了包含变体积弹性模量的系统数学模型。提出一种基于粒子群算法优化(PSO)的模糊自适应PID控制方法(简称PSO_FPID)。模糊逻辑推理在线调整PID控制器的比例、积分和微分系数,以粒子群算法实现对模糊控制比例因子和量化因子的参数寻优,两种方法的组合保证了系统最佳参数匹配下的自适应控制。同时,利用AMESim与Simulink联合仿真研究不同含气量的阀控缸模型在传统PID与PSO_FPID两种控制方法下的动态响应特性。结果表明:PSO_FPID综合了PID控制器高精度的优点和模糊控制器快速、适应性强的特点,能够有效抑制油液动态压缩特性的非线性影响,使系统具有良好的动、稳态特性。     

基于模糊自适应PID控制的桥式起重机定位防摆研究

指出了一种基于模糊自适应PID控制的桥式起重机定位和防摆方法,通过找出偏差和偏差变化率与PID控制器3个参数之间的模糊关系,在运行中跟踪误差信号来动态改变控制器参数,以满足不同的偏差和偏差变化率对控制参数的不同要求,从而使被控对象有良好的动静性能。仿真结果表明了该方法的可行性及较好的鲁棒性。     

模糊自适应PID液压变桨距控制

风力发电机变桨距系统具有非线性、参数时变性等特点,结合PID控制和模糊控制原理,提出了模糊自适应PID液压变桨距控制;在所设计的电液伺服控制实验平台上进行了控制仿真试验;试验结果表明模糊自适应PID比常规PID控制具有良好的静动态性能,能对风力机桨距角进行有效地控制。     

基于遗传算法的无刷直流控制器的设计

针对传统PID控制的无刷直流电机调速系统整定不良﹑性能欠佳和对运行工况的适应性差的缺点,提出一种模糊PID与基因演算相结合的控制算法,对模糊控制规则进行优化,使其更加合理。依托TMS320F2812强大的软件处理能力和硬件支撑,应用于无刷直流电机调速控制系统中,并对转速和相电流进行了仿真验证。仿真实验表明,与传统的PID方法相比,有效地改善了系统的动静态性能。     

An integrated control framework for flexible manufacturing systems

This paper presents the design, development, and implementation of an integrated control framework that provides a real-time supervisory control model with limited look-ahead capability for flexible manufacturing systems. Control goals and policies are modeled and characterized by a fuzzy rule base, which is integrated with the control model. The framework consists of a finite state machine generator and a controller. The generator model is equipped with an output function and output sets. The controller model has a four-stage decision-making structure. The controller monitors performance measures of the manufacturing system and reacts according to the changes in the system states in order to keep the performance measures at desired levels. The integrated framework has been implemented on a software platform in order to validate its effectiveness. The performance of the framework has been tested on a hypothetical flexible manufacturing system using a simulation .