带前馈的PID控制回路的控制器性能评估

提出一种评估带前馈的PID控制回路的控制器性能的方法.该方法通过求取在最优前馈和反馈控制器作用下的最小过程输出方差,并将其与实际的输出方差比较,以评估控制器的性能,同时可以得到实现该最小方差的最优PID控制器的参数.仿真结果表明,引入前馈作用可以改善PID控制回路的性能,并且采用本文提出的评估方法可以得到一个合理的评估结果.     

PID最小方差控制在参数整定中的应用

流程工业的控制回路中90%以上都使用PID控制器,在线PID参数整定方法一直是一个有很大意义却比较难解决的工程问题。PID最小方差性能评价常用于评价控制性能,然而其得出的最优PID参数往往并不适用于实际系统,当出现问题时需要重新加阶跃响应整定PID参数。将PID最小方差控制和系统传统的动态性能指针评价方法结合使用,通过系统传统的动态性能指针的要求给出PID参数的取值范围,再根据过程输出方差随PID参数变化而变化的趋势整定PID参数,该方法在实验装置的参数整定中得到了验证。     

基于微粒群优化的鲁棒PID控制器参数整定方法研究

针对复杂工业过程中存在的一类模型不确定问题,提出一种新的鲁棒PID控制器参数整定方法.通过将鲁棒PID控制器的参数整定问题转化成一个max-min优化问题,利用微粒群优化(PSO)的协作算法对之进行求解,能获得某种鲁棒性能指标最优的PID控制器.对连续搅拌反应釜系统的实例仿真结果表明:与其它典型鲁棒PID控制器设计方法相比,本方法得到的PID控制器具有更强的鲁棒性和抗干扰能力,当过程操作范围发生大的变化时,利用本方法设计的鲁棒PID控制器能获得满意的结果.     

基于优化线性回归方法的流程工业控制性能评价

控制性能评价理论能够有效利用工业过程数据实时检测控制器运行情况,对控制系统早期存在的问题进行识别。在基于线性回归方法的基础上,添加遗忘因子对算法进行优化,并于流程工业典型精馏环节中进行验证。验证结果表明,优化后的算法避免了用于求解丢番图方程的复杂计算,并可以更好地估计控制系统的最小方差。     

工业过程PI控制器性能评价

针对工业过程的PI控制器,提出了一种控制器性能评价的新算法。该算法以广义最小方差为目标,推导出最优PI控制器参数。以该最优控制器为基础,得到PI控制下系统的最优控制性能。然后,以最优控制的输出为基准,进行性能评价,并给出了性能评价的可操作步骤。最后通过仿真实验验证了该方法的有效性。     

纯碱装置碳化塔温度的模糊控制仿真研究

针对纯碱装置碳化塔温度的控制过程,利用参数自整定PID模糊控制方案进行了该控制过程的仿真研究。结果表明过程参数发生变化时,该类模糊控制器能有效地进行PID参数的修正,较好满足了工程控制要求。其控制效果优于常规PID控制器。     

典型大时变时滞系统神经网络模糊PID控制及应用

针对典型大时变时滞系统,设计了一种基于神经网络的模糊PID控制器.该控制器综合模糊逻辑、神经网络与PID调节的各自优点,既具有模糊控制简单和有效的非线性控制作用,又具有神经网络的学习和适应能力,同时还具备PID控制的广泛适应性.该控制器能实现系统参数大范围失配情况下的闭环鲁棒稳定,并使闭环系统达到设定值无静差跟踪及满意的动态性能.     

基于DSP Builder的直流力矩电机模糊PID控制

为弥补常规PID控制方式在控制直流力矩电机转速方面的不足,提出一种模糊PID控制技术。给出了模糊PID控制算法模型及其流程。运用DSP Builder库模块搭建了模糊PID控制器的系统模型,并进行了仿真分析和转速控制实验,结果表明:模糊PID控制器获得的主要控制品质参数均优于常规PID控制器,当被控对象参数和结构发生较大变化时,模糊PID控制器的响应曲线与各动态特性参数未发生较大变化,较好地保持了系统的稳定性,达到设计要求,且仿真与实验结果一致。     

风力发电机组恒功率无模型自适应变桨距控制

风力发电系统是一个非线性、强耦合的系统,其风速的扰动性极强。无模型控制基于系统特性值动态估计,优化内部参数可使系统克服时变和非线性,具有比PID更好的抗干扰能力,且更适用于非线性、强耦合系统。最后,对比了在阶跃和随机风速下无模型与PID控制器的控制效果,并进行仿真研究,结果表明无模型控制能更好地保持发电机功率恒定。     

基于自适应模糊PID的注塑机温度控制及仿真

为了对注塑机温度精确控制,针对注塑机温度在传统比例积分微分(PID)控制系统中存在的控制偏差大、调节速度慢等诸多不足的现状,提出将模糊控制器和PID控制器相结合,构造成一个自适应模糊PID控制器,运用MATLAB软件建立传统PID和自适应模糊PID控制器模型,对机筒温度进行仿真对比。设定200℃为给定温度,最终仿真结果显示,与传统PID控制器相比,自适应模糊PID控制器实现了注塑机温度的实时控制,达到了超调量小,升温快速及稳态无误差等要求。表明了自适应模糊PID控制器比传统PID控制器对温度的控制效果更加良好。     

Control performance monitoring — a review and assessment

In this paper we present an overview of current status of control performance monitoring using minimum variance principles. Extensions to PID-achievable performance assessment, trade-off between performance and robustness, and trade-off between deterministic and stochastic performance objectives are discussed. Future directions are pointed out for research and practice with regard to root-cause diagnosis, plant-wide performance assessment, multivariable assessment, adequacy assessment of existing control strategies, performance assessment of model predictive control, and the use of intelligent field devices and artificial intelligence to form a systematic diagnostic methodology. A brief tutorial on performance assessment is given in the appendix with an industrial process example.     

复杂厚壁汽车塑件精密成型工艺优化研究

以塑件最小体积收缩量为优化目标,以模具温度、保压时间、保压压力和熔体温度为优化变量,采用BOX(Box Behnken Design)二阶响应曲面法,结合方差分析技术,建立了高适配性体积收缩响应面优化模型,进而优化得出了最优工艺参数组合,通过计算机辅助工程(CAE)分析与成型实验验证,验证表明塑件的体积收缩量减少约8 %左右,满足塑件高精确装配要求,证明了研究工艺优化技术方法的可行性和可靠性。     

Optimizing multiple qualities in as‐spun polypropylene yarn by neural networks and genetic algorithms

This investigation considers a quantitative procedure for determining the values of critical process parameters in melt spinning to optimize the qualities of denier, tenacity, breaking elongation, and denier variance in as‐spun polypropylene yarn. An orthogonal array in the Taguchi method defines the minimum set of parameter‐level combinations that are experimentally tested. The significant process parameters, namely the third extruder barrel temperature, spinning temperature, metering pump speed, and take‐up velocity, are identified on the basis of the analysis of variance and F test. After a confirmation experiment is conducted to ensure the reproducibility of the experimental results, the back‐propagation neural network establishes a continuous system linking 10 process parameters and four qualities. The technique for order preference by similarity to an ideal solution can be used to obtain a performance measure for assessing multiple qualities. The genetic algorithm attempts to find parameter values for optimizing the quality performance, including the denier, tenacity, breaking elongation, and denier variance. Finally, the experimental results demonstrate that the smallest denier, largest tenacity, smallest breaking elongation, and second smallest denier variance of as‐spun polypropylene yarn can be achieved with the proposed approach in melt spinning. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 2532–2541, 2006     

基于广义最小变差基准的多变量控制性能评估方法

This paper is concerned with the control performance assessment based on the multivariable generalized minimum variance benchmark. An explicit expression for the feedback controller-invariant (the generalized minimum variance) term of the multi-variable control system is obtained, which is used as a standard benchmark for the assessment of the control performance for multi input multi output (MIMO) process. The proposed approach is based on the multivariable minimum variance benchmark. In com-parison with the minimum variance benchmark, the developed method is more reasonable and practical for the control performance assessment of multivariable systems. The approach is illustrated by a simulation example and an industrial application.     

二氯苯与二苯胺体系汽液平衡数据测定及关联

采用色谱法测定二氯苯在二苯胺中无限稀释活度系数,并采用单参数法关联W ilson方程中模型参数;测定二氯苯之间的二元体系汽液平衡数据,采用三对二元体系模型参数关联对二氯苯-邻二氯苯-二苯胺、间二氯苯-邻二氯苯-二苯胺及对二氯苯-间二氯苯-二苯胺体系的汽液平衡数据,并与实验值比较;采用5对二元体系模型参数结合四元体系的汽液平衡实验数据,用最小方差法关联四元体系中第6对模型参数,并计算四元体系的汽液平衡数据,与实验值比较,实验与计算值误差均小于5%。实验和计算结果为混合二氯苯的萃取精馏分离提供基础数据。     

Parameter Sensitivity Analysis of a Spouted Bed

A three‐layer neural network, based on 192 sets of experimental data obtained by the authors, was built in order to simulate the influence of four main process parameters on the minimum and stationary spouting velocity and on the pressure drop in a spouted bed. The simulations with the neural net are in good agreement with experimental learning data, and the overall average absolute error is 5.43 %. The neural net was used in the framework of a Monte Carlo simulation using CRYSTAL BALL^®. The result of 100,000 trials revealed the percentage contributions of the process parameters to the variance of the selected state variables. Since there is significant uncertainty concerning the design equations of spouted beds, the results of this work should be useful for the design of such devices.     

Investigation of a pulsed laser ablation process for bonded repair purposes of CFRP composites via peel testing and a design-of-experiments approach

The present study aims to investigate an automatic material ablation process performed by a pulsed Ytterbium green fiber laser for bonded repair purposes of carbon fibre reinforced composites. The investigated process parameters are the scanning speed, the pulse frequency, the hatching distance and the hatching pattern whereas the targeted objectives are the material removal rate as well as the quality of adhesion as characterized by a novel composite peel test. The use of a green laser, if properly implemented and optimized, turns out to offer a series of advantages. Not only it allows the precise, controllable and automatic -without human intervention-material ablation but it can change the morphology of the CFRP surface through micro-machining effects such as the creation of novel highly regular micro-structural formations that significantly enhance bonding. We provide with experimental evidence that this is not always the case but happens only for specific levels of the process parameters. A design of experiments approach is implemented to search as effectively as possible the process parameters space. We utilize a Box-Behnken four-level factorial design to define the minimum number of experimental trials and build an appropriate test matrix. Analysis of variance is finally implemented to assess the influential parameters. Finally, the set of parameters that optimize the objective of simultaneously high peel strength and material removal rate are identified following a response surface methodology.     

Effect of gravure process variables on void area in shrink film

The gravure print quality on shrink film depends on process parameters and is fairly gaged by minimum print defects such as voids. The visibility of these defects is visually disturbing and could result in product rejection. This article investigates the effect of process parameters such as viscosity, speed, hardness, and line screen frequency on ink transfer from recess gravure cells and hence on print voids in an attempt to minimize them. A general full factorial design with the abovementioned four independent variables was analyzed by variance, main, and interaction effects. The results revealed line screen, hardness, and ink viscosity as the most influential factors in minimizing the defect. A regression model was developed to predict void area. The model was validated by conducting an additional 11 runs on the press. The predicted values from the model were in close agreement with the press results. The results showed a commendable decrease in the void area by 65%.     

Decentralized Control System Design under Uncertainty Using Mixed‐Integer Optimization

Decentralized control system design comprises the selection of a suitable control structure and controller parameters. In this contribution, the optimal control structure and the optimal controller parameters are determined simultaneously using mixed‐integer dynamic optimization (MIDO) under uncertainty, to account for nonlinear process dynamics and various disturbance scenarios. Application of the sigma point method is proposed in order to approximate the expectation and the variance of a chosen performance index with a minimum number of points to solve the MIDO problem under uncertainty. The proposed methodology is demonstrated with a benchmark problem of an inferential control for a reactive distillation column. The results are compared with established heuristic design methods and with previous deterministic approaches.