Optimizing the dynamic performance of galvanometric scanners through advanced trajectory planning for laser material processing

Galvanometric scanners constitute fundamental actuators in precision laser manufacturing, yet inertia-induced tracking errors impose severe throughput limitations for μm-scale positioning tasks. This work presents a software-based trajectory predistortion that compensates for scanner dynamics without hardware modification, enabling immediate deployment across existing industrial systems. Model-based trajectory optimization uses regularized inversion with Butterworth filtering to generate pre-compensated command signals that counteract inherent system lag. Experimental validation demonstrates settling time reductions of 49.2% for 30 μm movements and 17.3% for mm-scale movements. The tracking error decreased by precisely 50% from 200 to 100 μs, independent of the movement amplitude. Industrial implementation for titanium porous transport layer fabrication achieved 38.1% throughput enhancement. This software-only approach requires no hardware investment and integrates seamlessly with existing control systems. The methodology generalizes to diverse scanner-based applications, where positioning dynamics constrain manufacturing throughput. Widespread adoption could significantly accelerate production across multiple industries utilizing galvanometric scanning systems, as the technique can maximize the performance from installed equipment bases without hardware replacement or extended qualification procedures.