用于锁模控制的改进型遗传算法仿真研究

Simulation of Improved Genetic Algorithm for Mode-locked Control

  • 摘要: 光学频率梳技术是推动真空计量技术实现创新性发展的有力工具。被动锁模光纤光频梳是产生飞秒光梳的主要手段,基于非线性偏振旋转(NPR)的被动锁模方式具有结构简单、输出脉冲窄的特点,其被应用于光频梳产生。为了解决NPR光纤激光器自动锁模问题,基于耦合非线性薛定谔方程组(CNLSE)构建激光器的动力学模型,提出并优化了新的遗传算法目标函数。通过评估锁模域在全域的占比,优化配置种群初始数量和迭代次数。通过数值仿真方法验证了新遗传算法的可行性,实现了激光器的自动锁模。该方法有助于推动NPR光纤激光器的工程化应用。

     

    Abstract: Optical frequency comb technology serves as a powerful tool driving innovative advancements in vacuum metrology. Passively mode-locked fiber optical frequency combs, a primary method for generating femtosecond frequency combs, have gained prominence due to their simplicity in design and ultrashort pulse output characteristics by utilizing the nonlinear polarization rotation (NPR) mechanism for mode-locking. However, due to the high nonlinearity of NPR fiber lasers, traditional control methods struggle to stabilize mode-locking. Additionally, the system is susceptible to environmental disturbances, and mode-locking failure often occurs after initial locking, significantly limiting its practical applications. The mode-locking principles of NPR fiber lasers are briefly introduced. A simulation model of the mode-locked laser is established using coupled nonlinear Schrödinger equations (CNLSE), and MATLAB software is employed to simulate the evolution of intracavity electric fields from initial white noise in the 0–0.1 normalized amplitude range to Gaussian pulses with peak amplitudes around 5. The characteristics of fundamental mode-locked pulses are analyzed and summarized. Building on this model, a genetic control algorithm is implemented to simulate the automatic mode locking process. The effectiveness of the genetic algorithm is validated by comparing results under different objective functions. Based on the fundamental mode-locked pulse characteristics revealed in simulations, the objective function is optimized. Through parameter traversal, the distribution of mode-locking points in the domain is illustrated, and the proportion of the mode-locking region in the entire domain is evaluated via random sampling to refine genetic algorithm parameters.This methodology holds significant potential for advancing the engineering applications of NPR-based fiber lasers.

     

/

返回文章
返回