Model predictive control for real-time microstructure control in laser heat treatment

Abstract

Metals’ surface microstructure can be altered through controlled heating and cooling of the surface using the laser heat treatment (LHT) method. Lasers have the advantage in this process of being able to heat treat specific regions of the workpiece without affecting the whole product. However, because a laser is being used, this process is extremely sensitive to changes in the process inputs and disturbances, which results in changes in the thermal dynamics and alterations in the peak temperature and cooling rate, in particular. These alterations have a direct effect on the material and its mechanical characteristics, such as hardness and hardening depth. Since these variations are caused by complex metallurgical phenomena, it is important to control the thermal dynamics in real-time. Real-time control systems are usually error-based and do not have the ability to predict the effect of the control action on the system, deal with constraints, or correlate the mechanical and material properties of the processed materials to LHT process parameters. Hence, the development of accurate model-based controllers is required. Therefore, a Model Predictive Control (MPC) algorithm is developed in this paper to control the thermal dynamics during the LHT process, e.g., the peak temperature, in real-time. This controller uses a finite difference thermal model to find the optimal process speed that results in the desired peak temperature. Moreover, consistent hardness and hardening depth will be obtained by closed-loop peak temperature control.