动态矩阵控制在非自衡系统中的应用

动态矩阵控制(Dynamic Matrix Contiol,简称DMC)算法是以对象的离散脉冲系数模型为基础的,过去的DMC算法只能适用于自衡系统.本文研究了DMC算法在非自衡系统中的推广应用.推导出一个既适用于非自衡系统,又适用于自衡系统的改进DMC算法.作者通过计算机数字仿真和在实验室液位系统上的实时计算机控制证实了此改进DMC算法的正确性和实用性.     

一种扰动自适应的鲁棒预测控制算法

针对实际生产中扰动的时变性,提出了一种扰动自适应的鲁棒预测控制（RAMPC）算法以提高扰动抑制性能。采用时间序列（ARMA）模型在线辨识系统的不可测扰动,通过基于多次迭代思想的递推辨识算法（multi-iteration pseudo-linear regression,MIPLR）来保证在线辨识的质量和收敛速度。考虑到数据与辨识模型的不确定性,改用min-max形式描述MPC算法的控制作用优化命题,并将在线辨识过程中的误差数据引入min-max命题,使在线辨识与控制作用鲁棒优化求解紧密结合起来,提高算法鲁棒性。进一步将此min-max问题转换为一个等效的非线性min问题,并采用多步线性化方法实现快速求解,解决了传统min-max方法在线计算负荷高的问题。仿真结果表明了该算法的有效性。     

一种改进的DMC算法在网络控制系统中的应用

研究网络环境下控制系统时延的组成与产生机理,提出一种基于动态矩阵控制（DMC）模型预测算法的改进DMC算法。该算法充分利用动态矩阵控制（DMC）算法中冗余的预测输出序列和控制增量序列,在控制数据由于网络时延和丢包而无法及时到达执行器时,实现对网络时延和数据丢包的补偿。并通过实验证明改进算法的有效性。     

基于可行扰动的非线性预测控制实时迭代算法设计

针对非线性模型预测控制中滚动优化问题在线求解的困难,提出一种基于可行扰动的实时迭代优化算法。将可行扰动策略引入滚动优化中,保证算法快速收敛且具有提前终止能力。通过对运动小车以及连续搅拌反应釜的仿真研究,验证了该算法的有效性。     

基于DMC-PID控制的催化剂温控系统设计

通过对动态矩阵控制(DMC)算法和传统PID控制的分析,提出一个基于DMC-PID串级控制的催化剂温控系统。仿真结果表明:DMC-PID控制效果优于PID-PID控制;电流副回路采用PID控制,能够快速有效调节电流进而控制燃烧炉内温度;温度主回路采用DMC控制,克服了传统温控系统存在的超调量大、时延及滞后性等问题,避免了多种不可测扰动的影响。     

碳酸二甲酯生产首用静态混合管式技术

<正>由山东飞扬化工有限公司和沈阳化工大学联合完成的双扰动静态混合管式技术在碳酸二甲酯(DMC)生产中的开发和应用项目,2012年12月初通过泰安市科技局的成果鉴定。专家认为,该项目成果推动了以碳酸丙烯酯为原料生产DMC联产1,2-丙二     

改进的双模型结构RBF神经网络及其应用

提出了离线结构学习和在线权值校正相结合的双模型结构RBF神经网络,以离线学习和在线校正相结合的方式实现网络的自学习和自校正,满足了软测量仪表现场应用的要求。针对应用过程中出现预测误差过大的现象,通过对网络算法进行分析,研究影响网络预测精度的因素,在此基础上,提出了以K均值聚类法和递推下降算法相结合的RBF神经网络建模改进算法,仿真结果和实际应用证明了改进算法的有效性。     

基于改进YOLOv4算法的工程实验室信息化管理系统构建与应用

融合物联网技术、图像检测技术和深度学习算法,提出一种基于改进YOLOv4算法的工程检测实验室信息管理系统,通过WIFI+NB-IoT实现数据传递。为了弥补YOLOv4算法在尺度分布不均匀时精度降低的问题,提出利用IK-means++算法,引入ECA注意力模块和阶梯状特征融合网络结构对算法进行改进,算法改进后浮点运算数量、模型参数量分别降低了25.1%和43.1%,FPS和mAP分别提高6.8帧/s和3.65%,改进后算法不仅收敛速度更快,而且在不同光线环境下的设备检测准确率均高于改进前。将系统应用到工程实验室检测中,设备和环境各参数检测结果与标准仪器检测结果误差控制在±5%以内。     

基于差分进化粒子群混合优化算法的软测量建模

针对乙烯生产过程中,用传统方法难以直接完成对乙烯收率的在线测量的问题,提出了一种新型差分进化粒子群混合优化算法,建立了乙烯收率软测量建模。改进算法将优化过程分成两阶段,两分群分别采用粒子群算法和差分进化算法同时进行。迭代过程中引入进化速度因子进行算法局部收敛性判断,通过两个群体间的信息交流阻止算法陷入局部最优。对高维复杂函数寻优测试表明,算法的整体优化性能均强于基本粒子群算法和差分进化算法。应用结果表明,基于改进算法的软测量模型具有测量精度较高、泛化性能较好等优点。     

基于改进的时滞分析算法的化工过程故障定位

在现代化工过程中,故障在局部出现后往往会通过物流连接、控制系统的作用下传递到整个流程。识别故障的传播机理,诊断出故障的根本原因对于生产的经济性或安全性都具有重大的意义。时滞分析是一种基于数据的算法,具有不依赖机理模型,获得的结果易于解读等特性,被认为是一种很实用的故障识别算法。将小波降噪技术、全流程节点划分等方法与时滞分析算法相结合,可以较好地克服化工过程在线数据的强噪声特点以及模型中冗余时滞的干扰,改进的算法具有更好的鲁棒性,具有化工全流程诊断的能力。通过对TE模型的故障定位研究,结果显示该方法可对异常工况进行故障隔离,并能给出扰动传播路径,有助于故障机理的研究。     

Modified dynamic matrix control

DMC (Dynamic Matrix Control) has been used successfully in industry for the last decade. It can deal with constraints and unusual dynamic behavior directly. It also shows a good control performance for the servo problem. Relatively, it can’t reject disturbances systematically. We propose a modified DMC method to control the regulatory process more efficiently. The proposed DMC method makes the control output by subtracting the estimated disturbance from the control output of the original DMC. Here, the disturbance is estimated by a new disturbance estimator. It shows better control performances than the original DMC.     

采用Profibus现场总线的碱回收集成优化控制系统

提出一套基于Profibus现场总线的碱回收集成优化控制系统,该控制系统可使碱回收生产过程长期处于稳定高效、低成本的状态下运行.重点阐述了系统中采用的黑液波美度在线软测量、燃烧过程步进式搜索自寻优优化、苛化工段石灰加入量的动态矩阵控制(DMC)等测量和优化控制算法.     

ON-LINE ROBUST CONTROL BASED ON AN EXTERNAL LOOP

A method of on-line robust control based on an external loop was proposed. The control structure was set up by adding an external loop to the conventional feedback control system. A filter was implemented in the external loop for robust control. Design of the filter was based on a robust stability index (RSI) which was on-line determined. The proposed robust control was carried out without changing the original feedback design of the control system.     

Characteristic equations and robust stability of a simplified predictive control algorithm

In predictive control, control calculations are done such that the difference between the desired and the predicted response of the process is minimized. The number of points on the prediction horizon at which the error is minimized and the number of future control moves considered affect the on-line computational effort involved in the solution of the constrained optimization problem. Earlier papers have shown that the control performance obtained using the DMC algorithm can also be obtained by using a simplified algorithm where the error is minimized at one point and one future control move is calculated. Because of its computational advantages, the simplified algorithm is analyzed further in this paper. Its transfer function is compared with the transfer function of the DMC algorithm. Characteristic equations to select tuning parameters are presented. The paper also compares the robust stability of the simplified and the DMC algorithms on SISO and MIMO process models. The results provide additional support to the viability of the simplified algorithm and thus indicate that it is possible for some processes to benefit from predictive control with only modest computational resources.     

塑料挤出机主辅电机联动系统设计

本文在分析国内外挤出机生产线主辅电机同步联调特点的基础上,提出了一种实用的联调控制系统设计方案,控制系统设计采用纯硬件方式,可以广泛适用于国内未采用同步联调技术的挤出生产线,进行技术改造,对原有设备改动极小,具有很高的性能/价格比。     

Parametric and nonparametric model based control of a packed distillation column

Parametric and nonparametric model based control systems were applied to control the overhead temperature of a packed distillation column separating methanol–water mixture. Experimental and theoretical studies have been done to observe the efficiency and performance of both control systems. Generalized predictive control (GPC) system based on a parametric model has been tried to keep the overhead temperature at the desired set point. First, a parametric model which is controlled auto regressive integrated moving average (CARIMA) was developed and then the parameters of this model were identified by applying pseudo random binary sequence (PRBS) and using Bierman algorithm. After that this model was used to design the GPC system. Tuning parameters of the GPC system have been calculated using the simulation program of the packed distillation column. Using the predicted parameters, experimental and theoretical GPC systems were found very effective in controlling the overhead temperature. Dynamic matrix control (DMC) system based on a nonparametric model has been used to track the overhead temperature of the packed distillation column. For this purpose, a nonparametric model known as the dynamic matrix was determined using the reaction curve method. A step change in heat input to the reboiler was applied to the manipulated variable and the temperature of the overhead product was observed. After that, the dynamic matrix was used to design the DMC system. Several calculations have been done to define the DMC control parameters. The best values of the tuning parameter were used to realize the DMC system for controlling the overhead temperature experimentally and theoretically. In the presence of some disturbances, the DMC system gives oscillation and offset in experimental studies.     

电厂直接空冷系统汽轮机背压的控制方法

针对传统PID对直接空冷系统背压控制效果差的问题,提出一种基于动态矩阵控制算法的直接空冷系统汽轮机背压控制方法。根据动态矩阵控制算法建立了背压控制器模型,并将它与PID控制的背压控制效果进行了仿真对比,结果表明:与传统PID控制相比,动态矩阵控制算法的响应更快、更稳定。     

基于推断模型的工业气相聚乙烯装置多牌号质量指标在线控制

针对气相法聚乙烯装置生产中的缺乏质量指标在线测量、大时间滞后和频繁的牌号切换等特性,基于质量指标推断模型,提出一种基于质量指标推断模型的多牌号质量指标在线控制方法。所提方法已成功应用于中石化某气相聚乙烯装置,长周期的运行结果证实了所提方法可以有效地减少产品质量波动,减轻了操作人员的工作强度,取得了显著的经济效益。     

阶梯式多变量DMC分散优化算法及工程化实现

提出基于状态空间模型的阶梯式多变量动态矩阵控制分散优化算法,使计算量大大减少,并在自行研制的先进控制平台上,实现了这种算法.该算法的工程化实现方法,使用户可以方便地构建自动控制系统并实施多变量动态矩阵控制.对双容水箱的控制实验表明,该控制算法对具有多变量、时滞、耦合和不确定性的复杂对象,具有良好的控制效果.