A method for real-time temperature control of injection molding machine

Abstract

The invention discloses a real-time control method for the temperature of an injection molding machine. The control method includes the following steps: S1, modeling the temperature control system of the injection molding machine; S2, performing feedback on the temperature control system model by using a fuzzy neural network algorithm and a chaotic variation algorithm Optimize the parameters; S3, design the PID temperature controller of the chaotic fuzzy neural network injection molding machine; S4, simulate the experiment and analyze the simulation results; this method is based on the SA600 / 100 model injection molding machine. The algorithm is compared with the chaotic fuzzy neural network algorithm proposed in this paper, and the simulation experiment improves the sensitivity and control accuracy of the whole system.

Description

technical field [0001] The invention belongs to the technical field of automatic control, and in particular relates to a method for real-time temperature control of an injection molding machine. Background technique [0002] Plastic has become one of the four most important materials used by human society. The injection molding machine is a processing machine that heats the polymer raw material through the barrel of the injection molding machine to the temperature required for production, and turns it into a molten state, and then injects the polymer fluid heated to the molten state into the mold through the screw to cool and form it. Plastic injection molding is the most advantageous and main processing method of plastic products, accounting for about 1 / 3 of the total weight of polymer processing, so it occupies an important position in various fields of national economy. [0003] Generally, there will be a heating block with higher power at the front, middle and end of th...

AI Technical Summary

Problems solved by technology

Due to the different heating elements of various injection molding machines and the different technological levels of various types of injection molding machines, it is difficult to control the temperature to achieve a high temperature rise rate and temperature accuracy. The traditional PID control can only achieve positive The control accuracy of negative 7°C, the general improved control methods such as adaptive control method, fuzzy control algorithm, self-tuning control method, etc., although the various indicators of the temperature control system have been improved to a certain extent, they are more or less inferior. defect

For example, adaptive control must establish a relatively complete mathematical model to accurately control the input and output of the system. Fuzzy control requires a large amount of data support, which will greatly reduce the sensitivity of the system. The self-tuning method usually requires die-casting based on different principles and different processes The machine is controlled based on practical experience

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