Nonlinear model identification of dissimilar laser joining of S.S 304 and ABS using the Hammerstein–Wiener method

Abstract

The nonlinear system identification Hammerstein–Wiener method is used according to the experimental outputs of laser joining of Acrylonitrile Butadiene Styrene (ABS) and stainless steel 304 concerning the temperature distribution in different parameters of a pulsed laser, including welding speed, focal length, pulse duration, frequency, power and current. Limited linear and nonlinear models exist for such processes; however, due to restrictions and complex numerical calculations, their use in the real-time process control is not practical. An accurate model for the dissimilar laser joining of metals and plastic materials is essential for controller design and process automation. Compared to other popular nonlinear compensation techniques, this model has a simpler structure and needs fewer calculations. This paper considers the identification problems of Hammerstein–Wiener nonlinear systems by employing the gradient search technique. Seven available data sets for training and test phases in dissimilar input parameters were used, and root-mean-square error (RMSE), mean absolute percentage error (MAPE) and fitness value were calculated. The results indicated that the identified Hammerstein-Wiener model had acceptable performance in training and test phases and was in good agreement with experimental results.