Real-time optimal control method for deep neural network of injection molding machine

Abstract

The invention relates to the technical field of injection molding control, in particular to a real-time optimal control method for a deep neural network of an injection molding machine. The real-time optimal control method comprises the following steps of S10, establishing a dynamic mathematical model of an injection molding filling process of the injection molding machine, and converting a flow rate control problem of the injection molding machine into solving an optimal control problem with constraints; S20, carrying out iterative offline optimization solution on the dynamic mathematical model to generate an optimal state-control data set based on different initial state starting points; S30, training the deep neural network by using the optimal state-control data set, and the deep neural network learns a mathematical relationship of nonlinear mapping between an input state and an output optimal action; and S40, collecting current state data of the injection molding machine, inputting the current state data into the trained deep neural network, and outputting a control signal of the injection molding machine. According to the real-time optimal control method for the deep neural network of the injection molding machine, the optimal control is combined with the deep neural network, so that the current system state of the injection molding machine quickly responds to a current optimal input control signal of a servo valve motor of the injection molding machine in the next step.

Description

technical field [0001] The present invention relates to the technical field of injection molding control, and more specifically, relates to a real-time optimal control method of deep neural network of injection molding machine. Background technique [0002] Injection molding technology is a processing technology that transforms thermoplastic and thermosetting materials into plastic products. Injection molding machines are used as professional working machines for processing plastic parts and other plastic industries. 70% of plastic parts are produced by it. Important technical equipment in high-tech fields such as electrical and optoelectronic communications, providing important equipment support for high-end manufacturing industries such as new energy, new materials, energy conservation and environmental protection, and biomedicine. The injection flow rate of the molten polymer inside the injection molding machine is one of the key control parameters in the injection moldin...

AI Technical Summary

Problems solved by technology

Although the above scheme can convert the injection molding process parameters into control parameters, and the control parameters are directly used in the injection molding process, however, the above scheme adjusts the internal parameters of the injection molding machine offline for different conditions and working conditions, and the optimal input parameters are online. This process is time-consuming and labor-intensive, and the robustness is poor; once the initial conditions of the system change or the working conditions change temporarily, it is necessary to re-control the internal control of the system according to the new situation Correction and optimization of parameters, there are problems such as poor stability, long time, high cost, etc., and the online real-time feedback optimal control of the injection molding machine cannot be achieved

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