New techniques for modeling and control of GTA welding

Solutions to modeling the gas tungsten arc (GTA) welding process are presented. A scheme of modeling using an adaptive filtering approach is compared to a scheme using neural networks. The adaptive filtering scheme is a black-box modeling approach using finite impulse response filters to model the multivariable system. This approach assumes the system to be linear in the specified region of operation. The neural network approach has the potential to model nonlinearities in the system. Potential problems with this approach are also discussed. A solution to the control problem using a second neural network is also suggested