Abstract
In plastic injection molding, the ram velocity plays an important role in production quality. This paper introduces a new method, which is a combination of the current cycle feedback control and neural network (NN) learning, to control the ram velocity in injection process. It consists of two parts: a PD controller (current cycle feedback control) is used to stabilize the system, and the feedforward NN learning is used to compensate for nonlinear/unknown dynamics and disturbances, thereby enhancing the performance achievable with feedback control alone. The simulation results indicate that the proposed NN learning control scheme outperforms the conventional PD controller and can greatly reduce tracking errors as the iteration number increase.
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© 2004 Springer-Verlag Berlin Heidelberg
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Ouyang, G., Li, X., Guan, X., Zhang, Z., Zhang, X., Du, R. (2004). Ram Velocity Control in Plastic Injection Molding Machines with Neural Network Learning Control. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_26
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DOI: https://doi.org/10.1007/978-3-540-28648-6_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
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