精馏过程动态仿真建模

精馏过程的模型化与仿真在化工操作和工艺设计中具有重要的意义。对精馏塔进行动态数学模型的建立与仿真,不仅可以研究精馏过程在不同工况下的变化情况,而且还可以用于精馏塔的优化控制,进而提高精馏过程的生产效益。本文针对精馏塔操作过程,建立了基于平衡级假设和非平衡级假设的精馏过程动态机理数学模型,并对平衡级假设的模型进行了动态模拟。该模型从机理分析入手,进行合理的简化,模型的计算时间大大的缩短,从而使模型具有比较广泛的实用性。该模型采用的动态数学模型为METSH(质量平衡方程、相平衡方程、塔板效率方程、摩尔分数归一化方程、能量平衡方程)方程,通过计算METSH方程,可以模拟出精馏塔内温度、汽相流量、液相流量、汽相组分以及液相组分的变化趋势。通过仿真结果可以看到,该模型比较准确的预测了精馏塔中各个操作参数的动态趋势,与实际情况基本一致,其稳态结果与实际情况也基本吻合。该模型对于仿真培训及精馏过程的控制分析具有较高的理论研究意义和实际应用价值。     

多组分精馏塔灵敏度系数和灵敏度的计算

通过正确划分精馏过程的状态变量及决策变量,从精馏塔的过程方程入手,建立了多组分精馏塔灵敏度分析的数学模型及计算方法。通过该方法可方便地求出精馏塔名状态变量对决策变量的灵敏度及灵敏度系数,定量地确定设计裕量,从而为精馏塔控制方案的设计及实际生产操作提供依据。     

具有热泵的苯-甲苯精馏过程的建模与控制

研究了热泵精馏塔的建模与控制问题.针对苯-甲苯精馏过程,采用逐板计算的方法进行动态机理建模;在热泵端,基于能量守恒定律等热力学方程建立了热量传递模型.通过对仿真模型结果的分析,研究了热泵精馏塔系统的特性.为了研究热泵精馏塔的控制问题,通过对动态机理模型的阶跃测试和辨识,获得了控制模型.对热泵精馏塔系统,按照单变量PID控制和多变量DMC控制两种结构,分别设计控制系统,通过仿真研究对比了两种控制方案的性能.     

基于Aspen Plus的聚甲氧基二甲醚精馏过程模拟分析

在装有θ环填料的精馏塔内进行了聚甲氧基二甲醚精馏实验。利用化工流程模拟软件.AspenPlus对聚甲氧基二甲醚精馏过程进行模拟,首先,采用DsTWU简捷蒸馏模型,运用软件中NRTL、WILSON、UNIQUAC,3种物性方法对精馏塔进行了计算,得到了回流比、塔板数和温度等操作参数。接着,采用RadFrac严格精馏模型对精馏塔进行了验证,其计算结果与实验结果吻合良好,满足工艺要求。最后,对精馏塔的操作变量进行了灵敏度分析,讨论了进料位置、进料流率和回流比等参数对精馏分离要求与能耗的影响,并确定了最优化方案,即:进料板为第50块,进料流率为35 mol/h,回流比为6。     

节能型甲基异丙基酮精馏过程的控制研究

在酸-醛法合成甲基异丙基酮(MIPK)的反应粗产物中,水与MIPK、二异丙基酮(DIPK)等均形成共沸物,使得MIPK的分离精制变得非常困难,文中采用剩余曲线图法对丙酮-MIPK-水三元物系进行分析,提出了通过利用中间分离器在一个精馏塔中实现丙酮和水同时脱除的节能型精馏过程,并运用奇异值分解(SVD)方法对提出的节能型精馏过程进行分析,选择了适宜的控制方案,建立了相应的动态模拟模型,对控制系统的动态特性进行了分析.结果表明,文中提出的控制方案具有较好的抗扰动能力.     

动态流程模拟及其在精馏塔的操作分析中的应用

采用HYSYS流程模拟软件,对丙烯丙烷精馏塔进行动态流程模拟,分析了丙烯丙烷精馏塔在操作条件变化和进料流量及进料成分干扰变化时,整个塔的动态响应变化过程,研究了常规PID控制方案以及通常的先进控制方案所存在的问题,为改进的集实时优化与先进控制于一体的控制方案设计提供了依据。     

精馏塔的机理-神经网络混合建模

酒精精馏过程是一个复杂的化工过程,动态响应缓慢,内在机理复杂,参数间相互关联.为了解决精馏塔机理模型精度低和神经网络模型外推能力差的缺点,同时也为了精馏塔的先进控制提供一种可靠的先进模型,针对试验室酒精精馏塔,充分发挥机理模型和神经网络模型的特点,建立一种基于机理模型和神经网络补偿模型的酒精精馏塔的混合模型.最后对混合模型进行了仿真试验,仿真结果显示有很好的性能,精馏塔的精馏精度和精馏效率都得到了很大的提高.而且下一步正准备以此模型为基础,设计精馏塔的先进控制算法.     

精馏塔的控制

简述了精馏塔的精馏原理,从物料平衡和能量平衡的角度分析了精馏塔的控制要求,归纳出了几种基本的控制方案。并通过实例分析,对石油化工装置中常用的两种精馏段控制方案(物料平衡控制和能量平衡控制)进行了分析和比较,提出了作者的观点。     

甲醇精馏系统模拟与优化

本文应用过程模拟软件Aspen Plus,采用Wilson和PSRK相结合的物性方法,实现了对某厂甲醇四塔双效精馏系统的模拟.为降低生产成本,本文通过对系统模拟与分析,对生产的工艺流程进行进一步改进,并提出3个优化方案:(1)增加加压精馏塔侧线采出送常压精馏塔作为进料;(2)对常压精馏塔塔底和回收塔塔底部分废水进行循环;(3)采用加压精馏塔与预精馏塔双效精馏.经过模拟计算,改进后的新工艺流程在保证甲醇产品的产量与质量的前提下,共能节省公用工程热量21173 kW,节省公用工程冷量16268 kW,节省工业用水10375 kg/hr,污水处理量减少10 375 kg/hr.本文所选用的单元操作模型及物性方法对于模拟甲醇精馏系统是准确可靠的,因此本文所提出的优化方案能为甲醇工业生产节能、节水以及减少废水排放的改造和新工艺流程的开发提供理论依据.     

基于Matlab/Simulink的乙烯精馏塔多变量预测控制仿真研究

乙烯精馏系统是一个典型的多变量系统,乙烯精馏塔也是十分复杂的精馏塔,国内大部分乙烯装置的控制停留在PID控制的基础上,而聚合级乙烯的标准对乙烯产品的纯度要求很高,大部分装置为了使乙烯产品的纯度合乎要求,一般以高于标准的要求对塔进行控制,势必造成浪费,使经济成本上升.为了实现对乙烯产品的卡边控制,为开发合理的多变量预测控制方案奠定基础,本文开发了乙烯精馏塔的动态仿真平台,并以Matlab/Simulink为基础开发了多变量预测控制仿真平台,对乙烯精馏装置的多变量预测控制进行了一系列的仿真研究.     

Computer simulation and dynamic modeling of a quadrupedal pronking gait robot with SLIP model

In this study, a quadrupedal pronking gait robot modeling was carried out with Spring Loaded Inverted Pendulum model in stance phase. This is achieved by solving a natural problem in which the main goal is to enable the robot to walk and run in a stable condition regardless of the environmental conditions. In order to solve this problem, dynamic model and control of a quadrupedal robot were realized for a pronking gait. The stance and flight phase dynamic structures were solved in a sequential closed loop to obtain the equation of motion for pronking gait. Spring Loaded Inverted Pendulum model was used as a dynamic model to simplify the simulation, dynamic locomotion and experimental works of the system, and also to simplify the pronking gait concept. The quadrupedal robot with pronking gait was controlled by proportional-derivative control algorithm. As a result, all computer simulations have shown that the proposed control actions and methods are more effective and make the system control quite easy and successful.     

鳍-水舱综合减摇混沌系统控制方法研究

针对船舶减摇问题,对综合减摇系统动力学模型方程进行分析,可知该系统为混沌系统。利用相图与Lyapunov指数谱分析方法,验证该系统在特定条件下的混沌行为,通过选取合理受控参数,利用非线性反馈控制方法使系统的混沌行为得到有效控制。该方法使系统混沌动力学行为得到了改善,并保留了系统原有的动力学特性。将混沌搜索算法与蚁群算法相结合,实现对PID控制参数寻优,使混沌蚁群算法不仅具备较强全局优化能力,与此同时,系统的收敛速度得到提高,该控制系统的性能得到增强。     

Efficient reinforcement learning through dynamic symbiotic evolution for TSK-type fuzzy controller design

In this paper, efficient reinforcement learning through dynamic-form symbiotic evolution (DSE) is proposed for solving nonlinear control problems. Compared with traditional symbiotic evolution, DSE uses the sequential search-based dynamic evolution (SSDE) method to generate an initial population and to determine dynamic mutation points. Therefore, better chromosomes will be initially generated while better mutation points will be determined for performing dynamic mutation. The proposed DSE design method was applied to different control systems, including the cart-pole balancing system and the water bath temperature control system, and control problems were simulated on these systems. The proposed DSE method was verified to be efficient and superior for solving these control problems and from comparisons with some traditional genetic algorithms.     

Adaptive and optimal control of a non-linear process using intelligent controllers

A time-optimal control for set point changes and an adaptive control for process parameter variations using neural network for a non-linear conical tank level process are proposed in this work. Time-optimal level control was formulated using dynamic programming algorithm and basic properties of the solutions were analysed. It was found that the control is of bang–bang type and there is only one switching. In this method, a mathematical step-by-step procedure is used to obtain the optimal valve position path with one switching and is trained by neural network, based on the back-propagation algorithm. The dynamic programming procedure allows the set point to be reached as fast as possible without overshoot. An adaptive system is also designed and proved to be useful in adjusting the trained parameter of the dynamic programming based neural network for the process parameter variations. A prototype of conical tank level system has been built and implementation of dynamic programming based neural network control algorithm for set point changes and implementation of adaptive control for process parameter variations are performed. Finally, the performance is compared with conventional control. The results prove the effectiveness of the proposed optimal and adaptive control schemes.     

Constrained nonlinear multivariable control of a fluid catalytic cracking process

In this paper, a nonlinear constrained optimization strategy is proposed and applied to the reactor-regenerator section of a fluid catalytic cracking (FCC) unit. A nonlinear dynamic model of the fluid catalytic cracking process was used for the dynamic analysis of the plant and nonlinear multivariable control system. The model realistically simulates the riser-reactor and the one stage regenerator by assembling the mass and energy balances on the system of reactions. The model results were tested in a real-time application and the results were used to provide the initial values for the nonlinear control system design. A dynamic parameter update algorithm was used to reduce the effect of large modelling errors by regularly updating the model parameters. The constrained nonlinear optimization algorithm and strategies were tested in real-time on the fluid catalytic cracking reactor-regenerator. The results compared favourably to those from a linear multivariable controller.     

流程工业生产调度与控制集成系统研究

本文根据流程工业生产控制系统的特点,对生产调度和监控系统的集成需求进行了分析,讨论了调度与监控系统的集成策略,建立了一种新型的集成系统模型框架,设计了静态调度器和动态调度器的结构,并从获得工程满意解的实际需求出发,分析了集成系统的约束参数和调度算法,为实现流程工业调度与监控系统的集成提供了一种新方法。     

Non-parametric modelling of a rectangular flexible plate structure

This research investigates the performance of dynamic modelling using non-parametric techniques for identification of a flexible structure system for development of active vibration control. In this paper, the implementation details are described and the experimental studies conducted in this research are analysed. The input-output data of the system were first acquired through the experimental studies using National Instruments (NI) data acquisition system. A sinusoidal force was applied to excite the flexible plate and the dynamic response of the system was then investigated. Non-parametric modelling of the system were developed using several artificial intelligent methodologies namely Adaptive Elman Neural Networks (ENN), Backpropagation Multi-layer Perceptron Neural Networks (MLPNN) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The performance of all these methodologies were compared and discussed. Finally, validation and verification of the obtained model was conducted using One Step Ahead (OSA) prediction, mean squared error (MSE) and correlation tests. The prediction ability of the model was further observed with unseen data. The results verified that the MLPNN converge to an optimum solution faster and the dynamic model obtained described the flexible plate structure very well. The non-parametric models of the flexible plate structure thus developed and validated will be used as the representation of the transfer function of the system in subsequent investigations for the development of active vibration control strategies for vibration suppression in flexible structures.     

On Technical Controllability and Decomposition of the Lagrangian Systems with Bounded Controls

Consideration was given to control of the plant obeying the second-order Lagrange equations. Stringent requirements on the dynamic characteristics of motion under bounded control actions were placed on the control system of this plant. The notions of technical controllability of the closed-loop system and autonomous technical controllability of the plant were defined. The conditions for autonomous technical controllability of the plant were established and used to prove that the mathematical model of plant motion can be decomposed into individual subsystems. The decomposable mathematical model underlies a control algorithm providing technical controllability of the closed-loop system in terms of the given set of technical requirements.     

基于LS-SVM的BTT导弹动态逆反演控制

基于LS -SVM理论、动态逆控制和反演控制方法,针对具有非匹配不确定性的BTT导弹非线性数学模型,设计了一种基于LS- SVM的BTT导弹动态逆反演控制律;对传统反演控制律设计的不足之处,采用LS- SVM法逼近BTT导弹控制系统中带有未知成分非线性函数,从而实现了无需精确数学模型的全新控制律,避免了因建模误差对控制带来的不良影响,在此基础上,利用李亚普诺夫方法证明了系统的稳定性和收敛性;仿真结果表明,文章所设计的控制律,对导弹控制系统中存在的不确定因素具有较强的鲁棒性和自适应性.     

电流型变流器的改进模型预测控制

传统的模型预测控制(MPC)采用脉冲响应的非参数模型作为系统的预测控制模型,计算量大,很难直接应用于实时控制系统.本文提出将传统的MPC进行改进,应用到电流型变流器(CSC)功率因数校正系统中.改进的MPC根据CSC控制量与被控制量的传递函数得出CSC的一阶差分方程作为预测控制模型,同时保留传统MPC反馈校正、动态优化等优点.将此改进的MPC与传统的PID控制进行对比研究,结果表明:改进的MPC用于电流型变流器,比传统的PID控制具有更好的鲁棒性和更快速的动态响应特性.