摘要
模糊PID控制器的参数优化至今仍是一个未得到完美解决的问题。利用灰狼优化算法优化模糊PID控制器的量化因子和比例因子,可以改善给定条件下系统的控制性能。通过球杆系统的阶跃响应实验,验证了基于灰狼优化算法的模糊PID控制器相对于传统模糊PID控制器、粒子群优化算法和遗传算法优化的模糊PID控制器在系统响应时间、超调量和调节时间等方面具有明显优势,有效提高了系统的控制性能。
The parameter optimization of fuzzy PID controller is still an unsolved problem.The use of grey wolf optimization algorithm to optimize the quantitative factor and scaling factor of fuzzy PID controller can improve the control performance of the system under given conditions.Through the step response experiment of the golf club system,it was verified that the fuzzy PID controller based on the grey wolf optimization algorithm has significant advantages over traditional fuzzy PID controllers,particle swarm optimization algorithms,and genetic algorithm optimized fuzzy PID controllers in terms of system response time,overshoot,and adjustment time,effectively improving the control performance of the system.
作者
胡智勇
龙祖强
古嘉盈
孙柯
HU Zhiyong;LONG Zuqiang;GU Jiaying;SUN Ke(College of Physics and Electronic Engineering,Hengyang Normal University,Hengyang 421002,China)
出处
《自动化与信息工程》
2025年第1期52-58,共7页
Automation & Information Engineering
关键词
灰狼优化算法
模糊PID控制器
参数优化
量化因子
比例因子
grey wolf optimization algorithm
fuzzy PID controller
parameter optimization
quantitative factor
scaling factor
