基于改进遗传算法的Buck变换器高性能MPC控制策略High-performance MPC control strategy for the Buck converter based on an improved genetic algorithm
巩昊辰,马彬
摘要(Abstract)：
针对DC/DC变换器在动态负载与参数摄动下难以兼顾瞬态响应与稳态精度，且传统模型预测控制（model predictive control, MPC）权重整定严重依赖经验的问题，提出一种基于精英保留（elite retention）与高斯变异（Gaussian mutation）改进遗传算法（genetic algorithm, GA）优化的MPC策略EGM-GA-MPC。首先，建立Buck变换器离散增广状态空间模型，以控制增量为输入，旨在从机理上消除稳态误差。其次，设计包含时间乘绝对误差积分（integral of time-multiplied absolute error, ITAE）指标与超调惩罚项的复合适应度函数，构建参数寻优框架。最后，引入精英保留策略抑制种群波动，利用高斯变异算子增强最优解邻域内的精细搜索能力，实现权重矩阵的高精度整定。MATLAB与STM32硬件在环实验表明，该策略显著优于传统MPC及标准GA-MPC，在最具代表性的48 V降压至24 V工况下，最大超调量抑制至0.90%，与对照组标准GA-MPC相比，调整时间缩短19.8%。结果证实了该策略在提升控制精度与鲁棒性方面的优势，尤其适用于对电压纹波要求严苛的场景。
关键词(KeyWords)： Buck变换器;模型预测控制;改进遗传算法;精英保留;高斯变异
基金项目(Foundation):
作者(Author): 巩昊辰,马彬
DOI: 10.16508/j.cnki.11-5866/n.2026.01.012
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