FPGA-based adaptive fuzzy speed control of welding robots with image processing techniques

Developments in the manufacturing industry and the rapid increase in the production need in the sector have led to the widespread use of welding robot systems in manufacturing industrial products. Automating the welding process through robots has increased the precision and quality factor in production, allowing robots to gain an essential place in the industry. In addition, robots have reduced the need for humans during welding, reducing the harm of bright light and toxic gases and contributing to increased safety. However, automating welding processes and reducing human control in production may lead to the emergence of uncontrolled structures against possible system errors. Therefore, it is critical that intelligent control units control the systems to maintain the quality parameters of robotic systems in production and increase their performance. In this study, it is aimed to minimize system errors that may occur due to material defects and external factors in welding operations performed by welding robots and to keep the welding quality at an optimum level. Based on this purpose, an adaptive system has been proposed in which the welding path is defined by sensors and the robot speed and torch position are controlled depending on the welding path geometry. As a result of the study, speed control of the robot depending on the welding path gap was achieved with an adaptive fuzzy logic controller using FPGA (field programmable gate array) on a prototype welding robot. Recommended for publication by Commission XII—Arc Welding Processes and Production Systems.