摘要
针对异步电机转速控制中存在的误差问题,提出一种基于改进粒子群算法优化模糊比例-积分-微分(PID)控制的方法。建立异步电机数学模型,引用模糊PID控制系统。通过改进传统粒子群算法中的学习因子控制参数,进一步提高了算法的全局搜索能力和收敛速度。采用改进粒子群算法来搜索模糊PID控制参数的最优值,使得模糊PID控制器在异步电机转速控制系统中发挥得更好,从而降低了跟踪误差。设置异步电机不同期望转速,利用Matlab软件对不同工况进行仿真,在不同转速条件下比较优化前和优化后模糊PID控制的电机转速跟踪误差。结果显示:优化后的模糊PID控制系统,能够快速地到达稳定时间,稳态误差变化幅度较小。优化后的模糊PID控制系统在异步电机转速控制中的应用,具有快速响应的优势,能够降低电机转速的跟踪误差。
The article proposes a method for optimizing fuzzy proportional-integral-derivative(PID)control based on improved particle swarm optimization algorithm to address the error problem in asynchronous motor speed control.A mathematical model of asynchronous motor was established,and a fuzzy PID control system was referenced.By improving the learning factor control parameters in traditional particle swarm optimization algorithms,the algorithm’s global search capability and convergence speed have been further enhanced.Adopting an improved particle swarm algorithm to search for the optimal values of fuzzy PID control parameters enables the fuzzy PID controller to perform better in asynchronous motor speed control systems,thereby reducing tracking errors.Set different expected speeds for asynchronous motors,simulate different operating conditions based on Matlab software,and compare the motor speed tracking error of fuzzy PID control before and after optimization under different speed conditions.The results show that the optimized fuzzy PID control system can quickly reach the steady time with a small variation in steady-state error.The application of optimized fuzzy PID control system in asynchronous motor speed has the advantage of fast response and can reduce the tracking error of motor speed.
作者
赵鹏展
郭鹏远
马骉
ZHAO Pengzhan;GUO Pengyuan;MA Biao(College of Information and Intelligent Manufacturing,Chongqing City Vocational College,Chongqing 402160,China;College of Intelligent Manufacturing Engineering,Chongqing University of Arts and Science,Chongqing 402160,China)
出处
《中国工程机械学报》
北大核心
2025年第5期758-762,共5页
Chinese Journal of Construction Machinery
基金
国家自然科学基金资助项目(51575245)
重庆市教育委员会科学技术研究计划青年项目资助项目(KJQN202203902,KJQN202303910)。
关键词
异步电机
模糊PID控制
改进粒子群算法
误差
仿真
asynchronous motor
fuzzy PID control
improve particle swarm optimization algorithm
error
simulation
