Neural Modeling for Crude Oil Blending
نویسنده
چکیده
Crude oil blending is an important unit operation in petroleum re ning industry. A good model for the blending system is bene cial for supervision operation, prediction of the export petroleum quality and realizing model-based optimal control. Since the blending cannot follow the ideal mixing rule in practice, we propose a static neural network to approximate the blending properties. By input-to-state stability and dead-zone approaches, we propose a new robust learning algorithm and give theoretical analysis. Real data is applied to illustrate the neuro modeling approach. Copyright c 2005 IFAC. Keywords: identi cation, neural networks, crude oil blending
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