RBF Neural Network in the Application of Synthetic Tower Temperature Decoupling Control Research

Abstract:

The chemical production is vital to the development of our country.It is greatly significant to improve the ammonia synthesis production control project and to increase the economic returns. In allusion to a controlled object with coupling characteristics,in this paper RBF neural network decoupling controller is designed to realize the decoupling control of the synthetic tower temperature. Through the comparison of the simulation test results, the scheme shows that it has a better control effect than the conventional PID decoupling control method, so, if the scheme could be used in the actual chemical production process, it shall have a certain value in use.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 491-494
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.491
• Online since: August 2013
• Authors: Zhe Zhang, Li Jun Hao, Bing Ma
• Keywords: Decoupling Control, RBF Neural Network, Synthetic Tower

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