Application Research of Pipe Racking System Based on Improved Fuzzy Neural Network PID Control

Abstract:

According to pipe racking system exist nonlinear characteristics and in order to get smooth velocity of the racking in moving process. This paper structures a new kind of fuzzy neural network PID which identifies the target model and also provides a non-linear relation model for dynamic programming. In addition, by adopting robust feedback controller, the stability of the closed-loop system and satisfactory control results in initial stage of fuzzy neural network learning are also guaranteed. And we analyze the error response curve of sine signal tracking, the experimental results show that the improved fuzzy neural network PID controller has a higher control performance. The control method has fast response speed, less overshoot and error, strong robust and can meet the requirements of the nonlinear system.

• Periodical: Key Engineering Materials (Volume 561)
• Pages: 448-453
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.561.448
• Online since: July 2013
• Authors: Jian Hua Song, Da Wei Cai, Xing Dong Zhu
• Keywords: Elman Network, Fuzzy Neural Network (FNN), PID Control, Pipe Racking System, Robust Controller

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