Robust Additive Manufacturing Performance through a Control Oriented Digital Twin

The additive manufacturing process control utilizing digital twins is an emerging issue. However, robustness in process performance is still an open aspect, due to uncertainties, e.g., in material properties. To this end, in this work, a digital twin offering uncertainty management and robust process control is designed and implemented. As a process control design method, the Linear Matrix Inequalities are adopted. Within specific uncertainty limits, the performance of the process is proven to be acceptably constant, thus achieving robust additive manufacturing. Variations of the control law are also investigated, in order for the applicability of the control to be demonstrated in different machine architectures. The comparison of proposed controllers is done against a fine-tuned conventional proportional-integral-derivative (PID) and the initial open-loop model for metals manufacturing. As expected, the robust control design achieved a 68% faster response in the settling time metric, while a well-calibrated PID only achieved 38% compared to the initial model.