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Neural-network-based predictive learning control of ram velocity in injection molding

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3 Author(s)
S. N. Huang ; Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore ; K. K. Tan ; T. H. Lee

In this paper, we develop a predictive learning controller for ram velocity of injection molding based on neural networks. We first introduce a model of describing the injection molding, including the time horizon and the batch index. The feedback control plus biased function is proposed for controlling this plant. More specifically, a radial basis function (RBF) network is used to approximate the biased function based on the time horizon. The weights in the RBF are determined by a predictive control scheme based on the batch index. For this algorithm, relevant convergence is investigated. Simulation results reveal that the proposed control can achieve our claims.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)  (Volume:34 ,  Issue: 3 )