Assembly control method based on long short-term memory neural network incremental model

Abstract

The invention provides a control method based on a long short-term memory neural network incremental model, and belongs to the technical field of intelligent control of information physical systems. According to the method, virtual models are established for a to-be-assembled product, an assembly robot and an assembly task entity which are on an assembly line through modeling software, and the movement pose of the assembly robot is accurately controlled on the basis of the dynamics principle; a feasible assembly scheme is planned through virtual assembly, real-time accurate mapping between thevirtual models and actual models is achieved, the actual assembly meets the error requirements of virtual assembly, so that the spatio-temporal consistency of the virtual models and equipment entityduring the movement process is maintained. According to the control method, the accuracy of a virtual assembly result can be improved, and it is ensured that the actual assembly is successfully completed.

Description

technical field [0001] The invention belongs to the technical field of intelligent control of cyber-physical systems, and in particular proposes an assembly control method based on a long-short-term memory neural network incremental model. Background technique [0002] The six-degree-of-freedom industrial manipulator is a robot that can move and rotate freely in three directions within the manipulator's range of motion and has six degrees of freedom. Because it can complete highly repetitive mechanical work, has a friendly user interface, is easy to operate, supports programming and external drive, and has flexible control, the application of this type of robot in assembly is increasing day by day. The six-degree-of-freedom industrial manipulator on the assembly line can learn its control parameters through agile and diverse sensors, so that the assembly speed is stable, and the positioning is accurate and predictable. [0003] Traditional virtual assembly mainly uses virtu...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the invention is to overcome the large motion time delay and low accuracy of the existing white-box model based on dynamics principle online simulation control virtual model and physical entity and the black-box model based on multi-layer perceptron neural network for physical entity and virtual model. Due to the low precision of the motion control, an assembly control method based on the incremental model of the long short-term memory neural network is proposed.