由于传统PID控制在复杂多变系统难以做到精确控制，因此结合PID控制与模糊控制策略应用于发电机组的调速系统与励磁系统，对船舶发电机组实现模糊PID控制。由于模糊控制的控制规则取决于人为主观经验，且模糊控制规则和隶属度函数需要大量实验与经验佐证，采取PSO粒子群算法对模糊PID控制中的隶属度函数进行优化。根据Matlab仿真平台模型搭建及分析，表明PSO粒子群算法优化后的模糊PID控制使得船舶柴油发电机组的调速系统与励磁系统更加优化稳定，具有良好的稳态与动态性能。
Because traditional PID control is difficult to achieve precise control in complex and changeable systems, the combination of PID control and fuzzy control strategy is applied to the speed regulation system and excitation system of the generator set to realize fuzzy PID control of the marine generator set. Since the control rules of fuzzy control depend on human subjective experience, and the fuzzy control rules and membership functions require a lot of experiments and empirical evidence, PSO particle swarm algorithm is used to optimize the membership functions in fuzzy PID control. According to the establishment and analysis of the Matlab simulation platform model, it is shown that the fuzzy PID control optimized by the PSO particle swarm algorithm makes the speed regulation system and excitation system of the marine diesel generator set more optimized and stable, and has good steady-state and dynamic performance.
2023,45(3): 80-86 收稿日期：2022-01-19
DOI：10.3404/j.issn.1672-7649.2023.03.014
分类号：U665.1
基金项目：国家重点研发计划项目（2019YFE0104600）；国家自然科学基金资助项目（51909200）；工信部创新专项（103-42200022）
作者简介：武炜迪(1995-),男,硕士研究生,研究方向为轮机智能化及控制
