TY -的A2 Pilla Srikanth盟,阮Yufei盟- Gao, Huang AU - Li, Dequn PY - 2019 DA - 2019/07/01 TI - Improving the Consistency of Injection Molding Products by Intelligent Temperature Compensation Control SP - 1591204 VL - 2019 AB - Temperature stability is critical to the consistency of product quality in the injection molding process, and it is very necessary to improve the temperature control accuracy under dynamic conditions. However, due to the large time delay, strong coupling, and the dynamic characteristics existing in the system, it is not an easy task to achieve precise temperature control in the injection molding process. In this paper, a new intelligent temperature compensation control strategy for the injection molding process under dynamic conditions is proposed in order to solve two key problems in the compensation control strategy: the compensation time and compensation quantity. A data-based feedforward iterative learning control (ILC) algorithm is designed to learn the optimal compensation time. Once the optimal compensation time is learned, a deep Q-learning algorithm which combined Q-learning with an artificial neural network (ANN) is proposed to learn the optimal compensation quantity. An experimental platform is designed to validate the superiority of the proposed method. Experimental results show that the proposed method can effectively improve temperature control accuracy under dynamic conditions. Meanwhile, the product consistency has also been improved. SN - 0730-6679 UR - https://doi.org/10.1155/2019/1591204 DO - 10.1155/2019/1591204 JF - Advances in Polymer Technology PB - Hindawi KW - ER -