Development of fuzzy controller for inverter DC resistance spot welding using system identification

Abstract

Adaptive Resistance spot welding (RSW) technologies have been developed and applied within the automotive industry to improve the weldability of automotive steels, including conventional and high strength steels. Almost all adaptive RSW systems require an inverter DC RSW system as a platform because such a system can generate various types of current waveforms effectively with higher control frequency than an AC RSW system. In this work, a fuzzy controller for an inverter DC RSW system that can control constant current and more complex current waveforms was developed as a platform for adaptive control of RSW. This study used System identification (SI) to model the inverter DC welding system effectively. To optimize the fuzzy controller for the SI model, fuzzy scaling factors were optimized using a genetic algorithm. To apply the scaling factor of the fuzzy controller with the SI model to a real system, the scaling factors were adjusted using response surface methodology.