常减压装置的流程模拟优化及先进控制技术仿真研究

发布时间：2018-11-28 14:57

【摘要】：常减压蒸馏作为石油炼制行业的首道程序,其控制过程中有容量滞后和模型复杂的特点,参数调整也有很高要求。其装置核心设备的常压塔和减压塔都是多侧线塔,产品的控制品质要求高,系统内部相关性强,诸多参数不能作为调节参数。目前石化企业多采用早期进口的集成控制系统,有良好的可靠性,但所用的控制理念较落后,虽然一些企业对先进控制技术有所借鉴,仍难以适应不断发展的生产要求。流程模拟和先进控制技术成为提高常减压装置生产效率、优化生产工艺参数和提高产品质量的重要手段。本文阐述了ASPEN PLUS软件在某装置进行流程模拟中的应用。通过灵敏度分析,探讨各参数间的关系。对主要参数提出优化方案,并采用系统数据为随后的建模提供可行的依据。控制参数在高产品拔出率和油品质量的平衡点附近波动,通过状态分析对蒸汽量和加热温度进行优化,在保证生产效率和质量的同时达到节能降耗的目的。本文探讨了理论分析方法对被控对象建模方案的不足。利用ASPEN PLUS Dynamics建立常减压装置的动态模型,探索解决各参数间的内部干扰。利用Matlab计算和控制系统仿真的优势,借助ASPEN软件的模型参数和物性数据库,完成对被控对象模型的分析。采用系统辨识的方法,建立被控对象的RBF神经网络模型,经调整达到足够的精度。建立先进控制方案,探讨模糊神经预测控制在有大滞后作用下的多输入多输出系统的设计方案。利用Matlab以及Simulink与ASPEN PLUS联合,建立控制系统并进行模拟。探讨传统PID控制、模糊神经PID控制和模糊神经预测控制在常减压装置中应用的各类问题。本文研究结论对常减压装置的实际生产有一定的指导意义。
[Abstract]:Atmospheric and vacuum distillation is the first procedure in petroleum refining industry. It has the characteristics of capacity lag and complex model in its control process, and the adjustment of parameters is also very demanding. The atmospheric pressure tower and the decompression tower of its core equipment are multi-side line towers. The control quality of the products is high and the internal correlation of the system is strong. Many parameters can not be used as adjusting parameters. At present, petrochemical enterprises mostly adopt the early imported integrated control system, which has good reliability, but the control concept used is relatively backward. Although some enterprises have some reference to the advanced control technology, it is still difficult to adapt to the continuous development of production requirements. Process simulation and advanced control technology have become an important means to improve the production efficiency, optimize the production process parameters and improve the product quality. This paper describes the application of ASPEN PLUS software in the process simulation of a device. The relationship between the parameters is discussed by sensitivity analysis. The optimization scheme of the main parameters is proposed and the system data is used to provide a feasible basis for the subsequent modeling. The control parameters fluctuate near the equilibrium point of high product pull-out rate and oil quality. The steam quantity and heating temperature are optimized by state analysis to ensure the production efficiency and quality and achieve the purpose of saving energy and reducing consumption. In this paper, the deficiency of the theoretical analysis method to the modeling scheme of the controlled object is discussed. The dynamic model of atmospheric and vacuum equipment was established by ASPEN PLUS Dynamics, and the internal interference between parameters was solved. Based on the advantages of Matlab calculation and control system simulation, and with the help of the model parameters and physical properties database of ASPEN software, the analysis of the controlled object model is completed. The RBF neural network model of the controlled object is established by the method of system identification. The advanced control scheme is established and the design scheme of the fuzzy neural predictive control system with multi-input and multi-output system with large delay is discussed. Using Matlab, Simulink and ASPEN PLUS, the control system is established and simulated. This paper discusses the application of traditional PID control, fuzzy neural PID control and fuzzy neural predictive control in atmospheric and vacuum equipment. The conclusion of this paper has certain guiding significance for the practical production of atmospheric and vacuum equipment.
【学位授予单位】：燕山大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TE96

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