Control of a chaotic polymerization reactor: a neural network based model predictive approach.: An article from: Polymer Engineering and Science

This digital document is an article from Polymer Engineering and Science, published by Society of Plastics Engineers, Inc. on February 1, 1996. The length of the article is 5456 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.

From the author: Continuous polymerization processes may be very sensitive to small changes of the operation conditions. Continuous VA (vinyl acetate) solution homopolymerization reactors may present multiple steady-states and oscillatory behavior. A predictive control scheme that uses an internal model of the process is employed to stabilize such reactors and make them less sensitive to disturbances while subject to "hard" control action constraints. An ANN (artificial neural network) is used as the internal model, leading to fairly good predictions of the reactor behavior, including its multiplicities. The performance of the resulting control algorithm is compared to that of a "well-tuned" conventional proportional-integral-derivative (PID) controller.

Citation Details
Title: Control of a chaotic polymerization reactor: a neural network based model predictive approach.
Author: Mauricio B., Jr. de Souza
Publication:Polymer Engineering and Science (Refereed)
Date: February 1, 1996
Publisher: Society of Plastics Engineers, Inc.
Volume: v36 Issue: n4 Page: p448(10)

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