Design, evaluation, and implementation of a model-predictive control approach for a force control in friction stir welding processes

Abstract

Friction press joining is an innovative joining process for bonding plastics and metals without additives in an overlap configuration. A model-based approach for the design of an axial force controller for friction press joining is presented in this paper. A closed-loop control was set up on the machining center, in which the plunge depth was used as the controlling variable. In order to support the controller development, a nonparametric dynamic process model was developed via a data-based system identification. Subsequently, various control concepts were designed off-line and verified on the actual system. The most promising ones, a proportional controller, a controller created with the pole placement method, and a model predictive controller, were selected for further investigations. The three controllers were re-evaluated and compared by means of a defined input of disturbance variables and reference variables. The model predictive control (MPC) approach as well as the proportional controller were also tested for model uncertainties. For this purpose, different material combinations were joined using the different controllers. Thereby, it was shown that the MPC controller resulted in smaller standard deviations when encountering large model uncertainties. The investigations demonstrated the high potential of friction press joining of plastic components with metals. The results form the basis for future research, whereby the force can be specified as an additional input parameter instead of the plunge depth.

A Holistic, Model-Predictive Process Control for Friction Stir Welding Processes Including a 1D FDM Multi-Layer Temperature Distribution Model

“…In order to verify the transferability of the findings, we conducted validation tests with the material combinations PA6-GF30 with EN AW-6082-T6 and PPS-CF with EN AW-2024-T3, according to a previous study [3].…”

“…With this simple control, it was possible to keep the contact pressure constant. However, due to the nonlinear correlation between the current and the axial force, it was found that the control is only reliable above an axial force of 3500 N [3,14].…”

“…Based on the FSW system model of Zhao et al [17,18], Meyer et al [3] designed a system model for the FPJ process with aluminum and PE-HD (polyethylene with highdensity). Relying on this system model, the authors designed an MPC controller to regulate the axial force via the plunge depth.…”

“…For this reason, Meyer et al [3] dealt with a force-controlled process for FPJ. They demonstrated the potential of the optimal control concept by using a model predictive control (MPC) approach as an example.…”

“…According to Taysom et al [4], this approach has enormous potential, especially as a multi-variable control, but has never been proven. For this reason, the MPC force control of Meyer et al [3] will be extended by a temperature control, and possible interactions will be considered to guarantee a holistic, model-predictive, multi-variable control for FPJ. To this end, an MPC-based temperature control system is to be set up, and a model for calculating the temperature distribution in multi-layer systems is to be designed.…”