Control Strategy of Coiling Tension Based on RBF-NN Inverse System

Abstract:

Based on the study of coiler tension indirect control process, the purpose is to improve the control accuracy of the constant tension by the introduction of RBF neural networks and inverse system control theory. Depending on the physical characteristic of coiling tension control process, it could build the inverse system model for coiling tension control. By analyzing simulation results, this control strategy has great significance to the actual production.

• Periodical: Advanced Materials Research (Volumes 503-504)
• Pages: 1276-1279
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.503-504.1276
• Online since: April 2012
• Authors: Chao Wei Duan, Chao Zhang
• Keywords: Control Strategy, Inverse System, Neural Network (NN), Radial Basis Function (RBF)

References

[1] Chen Xiao-hong. Realization of inverse systems based on radial basis function network, Control and Decision . 1998, 12(3): 146-150.

[2] Cong Shuang. The Function Analysis and Application Study of Radial Basis Function Network, Computer Engineering and Applications . 2002, 38(3).

[3] Dai Xian-zhong ,  Liu Jun-feng. Neural network α th-order inverse system control method for nonlinear continuous systems. Acta Automatica Sinica, 1998, 24(4).

[4] Wu Re-bing, Li Chun-wen. Constructive inverse system method for general nonlinear systems. Control theory & applications, 2003, 24(3): 21-23.

[5] Li Chun-wen, LiuYan-hong . Feedback control of nonlinear singular systems with application to power systems: an inverse system method. Control Theory & Applications. 2007, 24(5): 29-30.