基于PSO优化算法的模糊PID励磁控制器设计

针对优化发电机励磁控制器控制问题，研究模糊理论及人工智能控制方法，建立数学模型分析励磁控制器，找到将粒子群算法与模糊PID相整合的励磁控制途径，并设计了适用于低压水轮发电机的励磁控制器.粒子群优化算法优化控制系统的初始参数，模糊PID完成对系统的动态控制.仿真结果表明，改进的控制器算法相比传统PID控制和模糊控制PID，响应速度较快（上升时间少于1 s），超调量小（超调量少于5%）.能够满足控制器快速、准确和稳定的要求，是一种先进的控制方法.
In order to optimize the excitation control problem of hydro-generator,a mathematical model was presented.With the fuzzy theory and the advanced intelligent optimization control method,a hydro-generator excitation controller was proposed based on the integration of particle swarm algorithm (PSO) and fuzzy PID.The initial parameters of controller were selected by PSO,and the system was dynamically controlled by FAPID.Finally,compared with the traditional PID control and fuzzy control PID control,the simulation results show that the fuzzy adaptive PID excitation control based on the particle swarm optimization algorithm has faster response speed (less than 1 second rise time) and smaller overshoot (less than 5% overshoot).The control system as an advanced control method can be faster,more accurate and stable.