Tension control system design of a filament winding structure based on fuzzy neural network

Authors

  • Zheng Li Hebei University of Science and Technology

Keywords:

FNN, neural network, control system, tension force, filament winding

Abstract

Filament winding products are widely used due to their quality, high strength and a series of advantages in the industrial areas. The process involves winding filaments under varying amounts of tension over a male mould or mandrel. The tension control product has become the most important object in the process. This study describes the tension force control of filament winding with fuzzy neural network controller design and its application to fiber reinforced plastics. The controller produces the error of the closed loop control system response and the actual system output for the desired tension system, instead of ordinary PID adjustment mechanism. Dynamic performance analysis of a traditional PID controller and fuzzy neural network controller is performed in detail using simulation and experiments. The results show that the system can not only exhibit desired dynamic performance but can also adapt to the wide range of speed and tension force changes by a proper servo motor and winding operation. This study provides the primary theoretical guide for the configuration design, optimization and control research of the FNN applications to industrial winding process.

Author Biography

Zheng Li, Hebei University of Science and Technology

Zheng Li received the Ph.D. degrees in electrical engineering and power electronics and electric drive from Hefei University of Technology, Hefei, China, in 2007. Since 2007, he has been a Professor and Vice Dean with the School of Electrical Engineering, Hebei University of Science and Technology. He is the author of more than 60 published papers. His current research interests include intelligent control; design, analysis, and control of novel motors and actuators and power electronics.

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Published

2015-01-21

Issue

Engineering Review, Vol. 35, No. 1

Section

Articles

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