An Adaptive Use Strategy for Solid-State Lasers by Combining Maximum Likelihood Estimation With Model Predictive Control

Solid-state lasers are widely applied in various fields, such as material processing, laser marking, and remote sensing. Long lifetime is always required for commercial solid-state lasers in practice. Thus, it is of great importance to carefully design the use strategy in order to efficiently utilize the available resources and prolong the lifespan of solid-state lasers. In this paper, the use strategy is investigated with the consideration of the performance degradation of solid-state lasers, for the general case that the values of the model parameters are all unknown. First, the degradation behavior of solid-state lasers is modeled on the basis of the Wiener process by taking into account normally distributed measurement errors. Then, an adaptive use strategy is proposed by combining maximum likelihood estimation (MLE) with model predictive control (MPC). The aim of the proposed use strategy is to maintain the actual output optical power of a solid-state laser at a stable and acceptable level by adaptively adjusting the input electrical power. Specifically, the estimates of the model parameters are updated based on the measured output optical powers up to the current time by applying MLE, and the input electrical power is optimized based on MPC. Finally, a numerical example is utilized to demonstrate the effectiveness of the proposed use strategy.