循环流化床的实时建模与控制

S. Valaboju, S. Pulluri, A. Davari, L. Shadle
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引用次数: 4

摘要

循环流化床(CFB)是一种复杂的非线性系统,在催化裂化、发电和选矿等领域得到了广泛的应用。与传统流化床相比,循环流化床具有界面接触好、返混少等优点。循环流化床是一种相对较新的迫使化学反应发生在化学和石油工业的方法。在缺乏常规方法推导可靠模型的情况下,我们利用神经网络设计了一个循环流化床模型,该模型具有通过非线性映射表征此类复杂系统的能力。主要目标是建立一个实时的神经网络模型来模拟和控制循环流化床。结果表明,该方法是成功的,并给出了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real time modeling and control of circulating fluidized bed
The circulating fluidized bed (CFB) is one of the complex nonlinear systems which has gained acceptance in a wide variety of fields like catalytic cracking, power generation and mineral processing. Compared with conventional fluidized beds, CFB have many advantages including better interfacial contacting and reduced back mixing. CFB is a relatively new method of forcing chemical reactions to occur in the chemical and petroleum industries. In the absence of conventional means to derive a reliable model, we have devised a model of the circulating fluidized bed using neural networks, which have the ability to characterize such complex systems through their non-linear mapping. The main objective is to develop a real time NN model to simulate and control the CFB. It has been shown that the attempt has been a successful and the results are presented.
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