Abstract
Sensorlesstension control of multi-motor synchronous system with closed tension loop is required in many fields. How to identify the knowledge of instantaneous magnitude of tension is key. In this paper the tension identification is managed on the base of stator currents and its previous values with neural network. According to the fundamental state equations of multi-motor system for tension control, the novel method of tension identification using neural network is presented .A multi-layer feed-forward neural network (MFNN) is trained by Back Propagation Levenberger-Marquardt’s method. Simulation and experiment results show that the system with tension identification via a neural network has better performance, and it can be used in many application fields.
Project supported by China ministry fund of education (20050299009) and Jiangsu Nature Science Foundation No.BK2003049.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Thiffault, C., Sicard, P., Bouscayrol, A.: Desensitization to Voltage Sags of a Rewinder by Using an Active Dancer Roll for Tension Control. In: IEEE International Electric Machines and Drives Conference, Hilton Palacio Del Rio, San Antonio, TX, USA, 15-18 May 2005, pp. 466–473 (2005)
Li, J.H., Shi, Y.Y.: Design of the Tension Control System for a Cloth Winding Machine. Mechanical Science and Technology, 1127–1129 (2005)
Ebler, N.A., Arnason, R., Michaelis, G., D’Sa, N.: Tension Control: Dancer Rolls or Load Cells. IEEE Transactions on Industry Applications 29(4), 727–739 (1993)
Song, S.H., Sul, S.K.: A New Tension Controller for Continuous Strip Processing Line. IEEE Transactions on Industry Applications 36(2), 633–639 (2000)
Chen, J.: The Mathematic Model of an Induction Motor and Its Speed Regulating System. National Defence Industry Press, Beijing (1989)
Chen, B.S.: Automatic Control System of Motor Drives. Mechanical Industry Press (1992)
Orlowska-Kowalska, T., Kowalski, C.T.: Neural Network Application for Flux and Speed Estimation in the Sensorless Induction Motor Drive. In: ISIE ’97, Proceedings of the IEEE International Symposium on Industrial Electronics 3, vol. 3, pp. 1253–1258 (1997)
Wu, J.B., Liu, G.H.: Rotor Flux and Speed Estimation of Induction Motor Using BP Neural Network. Power Electronics 4, 27–30 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, G., Wu, J., Shen, Y., Jia, H., Zhou, H. (2007). Tension Identification of Multi-motor Synchronous System Based on Artificial Neural Network. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_76
Download citation
DOI: https://doi.org/10.1007/978-3-540-72383-7_76
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72382-0
Online ISBN: 978-3-540-72383-7
eBook Packages: Computer ScienceComputer Science (R0)