Neural Model Reference Control of Laser Surface Heat Treatments

This paper introduces an innovative model reference neural controller for laser surface heat treatments, which allows to improve considerably the uniformity and final quality of the process, reducing the rejection rate and increasing significantly the productivity and efficiency of the process. Basically, the proposed adaptive controller allows to assimilate the complex system dynamics to a simple first order linear system, easily controlled by a conventional proportional, integral and derivative controller, PID, providing exceptional results.