NDLI: Neural network modeling and control of cold flow circulating fluidized bed

Content Provider	IEEE Xplore Digital Library
Author	Koduru, P. Davari, A. Shadle, L. Lawson, L.
Copyright Year	2004
Description	Author affiliation: Yale Univ., New Haven, CT, USA (Koduru, P.)
Abstract	Circulating fluidized beds (CFB) are a relatively new method of forcing chemical reactions to occur in chemical and petroleum industries. Compared with conventional fluidized beds, CFB have many advantages including better interfacial contacting and reduced back mixing. The recycle nature of CFB allows for a better process, but also makes modeling and understanding it many more times difficult. The plant under consideration is a cold-flow circulating fluidized bed (CF-CFB), meaning there is no combustion component in it. In the absence of conventional means to derive a reliable model, we have devised a model of the CFB using neural networks (NN), which have the ability to characterize such complex systems. This stems from their ability to approximate arbitrary nonlinear mappings. The main objective is to train a NN model and controller to simulate and control the CFB operation. It has been shown that a NN can be used effectively for the identification and control of nonlinear dynamical processes. Results are presented.
Sponsorship	American Automatic Control Council IFAC
Starting Page	1406
Ending Page	1411
File Size	370636
Page Count	6
File Format	PDF
ISBN	0780383354
ISSN	07431619
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Neural networks Fluid flow control Fluidization Solids Chemical industry Combustion Control systems Petroleum industry Recycling Nonlinear control systems
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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