Intelligent Control of Welding Gun Pose for Pipeline Welding Robot Based on Improved Radial Basis Function Network and Expert System

• Published in: International journal of advanced robotic systems Vol. 10; no. 2
• Main Authors: Tian, Jingwen, Gao, Meijuan, He, Yonggang
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 11-02-2013; Sage Publications Ltd; SAGE Publishing
• Subjects: Control systems; Expert systems; Genetic algorithms; Mutation; Neural networks; Nonlinear control; Pipelines; Pitch (inclination); Position sensing; Quality; Radial basis function; Robots; Welding; Intelligent Control; Radial Basis Function Network; Pipeline Welding Robot; Welding Gun Pose; Expert System
• ISSN: 1729-8806; 1729-8814
• DOI: 10.5772/55662

Since the control system of the welding gun pose in whole-position welding is complicated and nonlinear, an intelligent control system of welding gun pose for a pipeline welding robot based on an improved radial basis function neural network (IRBFNN) and expert system (ES) is presented in this paper. The structure of the IRBFNN is constructed and the improved genetic algorithm is adopted to optimize the network structure. This control system makes full use of the characteristics of the IRBFNN and the ES. The ADXRS300 micro-mechanical gyro is used as the welding gun position sensor in this system. When the welding gun position is obtained, an appropriate pitch angle can be obtained through expert knowledge and the numeric reasoning capacity of the IRBFNN. ARM is used as the controller to drive the welding gun pitch angle step motor in order to adjust the pitch angle of the welding gun in real-time. The experiment results show that the intelligent control system of the welding gun pose using the IRBFNN and expert system is feasible and it enhances the welding quality. This system has wide prospects for application.