催化裂化装置反应—再生部分预测控制研究
发布时间：2019-06-16 18:03
【摘要】：众所周知,原油是一种富含高价值但又极其复杂的混合物,主要是复杂的烃类和非烃类的混合物,因此必须通过各种加工手段才能使其转化为符合质量要求的产品。一般情况下,通过一次加工,采用常减压蒸馏后,能够得到10~40%的轻质油品,如汽油和柴油等等,而大部分余下的是利用价值比较低的重质油和残渣油。由于国民经济和国防需要大量的轻质油品,若不将重油进行二次加工,而只通过原油常减压蒸馏得到的轻质油是不能满足需要的。为了满足国民经济和国防的需要,从而使催化裂化技术得到了发展。反应-再生部分是催化裂化装置(Fluid Catalytic Cracking Unit,FCCU)的核心部分,关于催化裂化的优化与控制一直是研究者关注的焦点。针对反应-再生部分的控制研究,本文主要进行了如下几方面的研究工作:(1)FCCU反应-再生部分机理模型研究。本章对反应-再生部分的机理模型和求解方法进行了研究分析,建立了FCCU优化和控制所需的数学模型,然后对该模型模拟计算,实现了FCCU反应-再生部分的集总浓度与反应温度仿真分析。(2)FCCU反应-再生部分BP(Back Propagation,又称误差反向传播)神经网络建模。根据神经网络能够无限接近于实际对象的特点,通过MATLAB软件编程,建立FCCU反应-再生部分BP神经网络模型。所建模型的误差较小,且训练网络时收敛非常快。(3)FCCU反应-再生部分PID(Proportion Integration Differentiation,比例-积分-微分)控制方案设计及仿真。明确了FCCU反应-再生部分的控制目标、操纵变量和被控变量。利用MATLAB软件对反应-再生部分进行PID控制方案设计并仿真。结果表明,PID控制的控制效果良好,可以满足催化裂化的工业生产目标。(4)FCCU反应-再生部分预测控制设计及性能分析。通过探索模型预测控制(Model Predictive Control,简称MPC)的基本原理,将神经网络与预测控制结合,借助Simulink神经网络预测控制工具箱,进行反应-再生部分神经网络预测控制研究方案设计。并和PID控制相比较,结果表明,FCCU反应-再生部分的神经网络预测控制的控制质量明显优于PID控制,且振荡过程较短,超调量也较小,可实现FCCU反应-再生的优化控制。
[Abstract]:As we all know, crude oil is a kind of high value but extremely complex mixture, mainly complex hydrocarbon and non-hydrocarbon mixture, so it must be converted into quality products by various processing methods. In general, 10% of the light oil, such as gasoline and diesel oil, can be obtained by one processing and atmospheric and vacuum distillation, while most of the rest are heavy oil and residual oil with low value. Because the national economy and national defense need a large number of light oil products, if the heavy oil is not reprocessed, the light oil obtained only by atmospheric and vacuum distillation of crude oil can not meet the needs. In order to meet the needs of national economy and national defense, catalytic cracking technology has been developed. The reaction-regeneration part is the core part of catalytic cracking unit (Fluid Catalytic Cracking Unit,FCCU, and the optimization and control of catalytic cracking has always been the focus of researchers' attention. Aiming at the control of reaction-regeneration part, the main research work in this paper is as follows: (1) the mechanism model of FCCU reaction-regeneration part is studied. In this chapter, the mechanism model and solution method of reaction-regeneration part are studied and analyzed, and the mathematical model needed for FCCU optimization and control is established, and then the model is simulated and calculated to realize the simulation analysis of lumped concentration and reaction temperature of FCCU reaction-regeneration part. (2) FCCU reaction-regeneration part BP (Back Propagation, also known as error back propagation) neural network modeling. According to the fact that the neural network can be infinitely close to the actual object, the BP neural network model of FCCU reaction-regeneration part is established by MATLAB software programming. The error of the model is small, and the convergence of the training network is very fast. (3) Design and simulation of FCCU reaction-regenerated part PID (Proportion Integration Differentiation, proportional integral-differential) control scheme. The control objectives, manipulation variables and controlled variables of FCCU reaction-regeneration part are defined. The PID control scheme of the reaction-regeneration part is designed and simulated by MATLAB software. The results show that the control effect of PID control is good and can meet the industrial production goal of catalytic cracking. (4) Predictive control design and performance analysis of FCCU reaction-regeneration part. By exploring the basic principle of model predictive control (Model Predictive Control,), combining neural network with predictive control, and with the help of Simulink neural network predictive control toolbox, the research scheme of reaction-regeneration neural network predictive control is designed. Compared with PID control, the control quality of neural network predictive control in FCCU reaction-regeneration part is obviously better than that in PID control, and the oscillation process is shorter and the overshoot is small. The optimal control of FCCU reaction-regeneration can be realized.
【学位授予单位】：新疆大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TE96
，
本文编号：2500714
[Abstract]:As we all know, crude oil is a kind of high value but extremely complex mixture, mainly complex hydrocarbon and non-hydrocarbon mixture, so it must be converted into quality products by various processing methods. In general, 10% of the light oil, such as gasoline and diesel oil, can be obtained by one processing and atmospheric and vacuum distillation, while most of the rest are heavy oil and residual oil with low value. Because the national economy and national defense need a large number of light oil products, if the heavy oil is not reprocessed, the light oil obtained only by atmospheric and vacuum distillation of crude oil can not meet the needs. In order to meet the needs of national economy and national defense, catalytic cracking technology has been developed. The reaction-regeneration part is the core part of catalytic cracking unit (Fluid Catalytic Cracking Unit,FCCU, and the optimization and control of catalytic cracking has always been the focus of researchers' attention. Aiming at the control of reaction-regeneration part, the main research work in this paper is as follows: (1) the mechanism model of FCCU reaction-regeneration part is studied. In this chapter, the mechanism model and solution method of reaction-regeneration part are studied and analyzed, and the mathematical model needed for FCCU optimization and control is established, and then the model is simulated and calculated to realize the simulation analysis of lumped concentration and reaction temperature of FCCU reaction-regeneration part. (2) FCCU reaction-regeneration part BP (Back Propagation, also known as error back propagation) neural network modeling. According to the fact that the neural network can be infinitely close to the actual object, the BP neural network model of FCCU reaction-regeneration part is established by MATLAB software programming. The error of the model is small, and the convergence of the training network is very fast. (3) Design and simulation of FCCU reaction-regenerated part PID (Proportion Integration Differentiation, proportional integral-differential) control scheme. The control objectives, manipulation variables and controlled variables of FCCU reaction-regeneration part are defined. The PID control scheme of the reaction-regeneration part is designed and simulated by MATLAB software. The results show that the control effect of PID control is good and can meet the industrial production goal of catalytic cracking. (4) Predictive control design and performance analysis of FCCU reaction-regeneration part. By exploring the basic principle of model predictive control (Model Predictive Control,), combining neural network with predictive control, and with the help of Simulink neural network predictive control toolbox, the research scheme of reaction-regeneration neural network predictive control is designed. Compared with PID control, the control quality of neural network predictive control in FCCU reaction-regeneration part is obviously better than that in PID control, and the oscillation process is shorter and the overshoot is small. The optimal control of FCCU reaction-regeneration can be realized.
【学位授予单位】：新疆大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TE96
，
本文编号：2500714
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