Research and Application of Control Algorithm for Robot Intelligent Seam Tracking System

The traditional manual welding method is inefficient and unstable in quality, while the robot intelligent seam tracking system significantly improves the automation of welding operation and the stability of welding quality by integrating advanced robot technology, precision sensing technology and efficient control algorithm. In this paper, a multi-algorithm fusion control strategy is proposed, which combines the advantages of fuzzy control, neural network and adaptive control to realize accurate and robust weld tracking control. Fuzzy control module deals with the uncertainty in welding process, neural network module learns the relationship between weld position and welding quality based on historical data, and adaptive control module dynamically adjusts control parameters to adapt to environmental changes. Through the weighted average fusion strategy, the outputs of the three modules are effectively integrated to optimize the welding path. The application case analysis in the body welding production line of a large automobile manufacturing enterprise shows that the system can significantly improve the seam tracking accuracy, reduce the seam deviation rate, enhance the stability of the welding process and improve the production efficiency. This study not only verifies the effectiveness of multi-algorithm fusion strategy, but also provides reference for the design of intelligent control system in other industrial application scenarios.