1. 湖南大学 机械与运载工程学院,长沙,410082
2. 温州理工学院 智能制造与电子工程学院,浙江,温州,325025
[ "徐嘉亮,硕士研究生," ]
[ "陈逢军,教授,博士生导师," ]
纸质出版:2025
移动端阅览
徐嘉亮, 陈逢军. 天牛群改进模糊神经网络PID算法的混合式步进电机位置控制[J]. 机械科学与技术, 2025,44(12):2181-2190.
徐嘉亮, 陈逢军. Position Control of Hybrid Stepper Motor on BSO Improved Fuzzy Neural Network PID Algorithm[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(12): 2181-2190.
徐嘉亮, 陈逢军. 天牛群改进模糊神经网络PID算法的混合式步进电机位置控制[J]. 机械科学与技术, 2025,44(12):2181-2190. DOI: 10.13433/j.cnki.1003-8728.20230375.
徐嘉亮, 陈逢军. Position Control of Hybrid Stepper Motor on BSO Improved Fuzzy Neural Network PID Algorithm[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(12): 2181-2190. DOI: 10.13433/j.cnki.1003-8728.20230375.
为提高两相混合式步进电机的工作稳定性,实现对步进电机位置的精确控制,提出一种天牛群(BSO)改进模糊神经网络PID算法。首先,在建立两相混合式步进电机数学模型基础上,设计了基于BSO改进模糊神经网络PID控制器,采用BSO算法进行迭代寻优,找到合适的PID参数;其次,利用模糊神经网络对PID系数进行实时调整。最后,利用MATLAB软件进行仿真验证,并分别在搭建的步进电机位置闭环运动平台进行了阶跃响应实验和信号跟随实验。仿真和实验结果表明,相较于传统PID算法、BSO-PID算法以及模糊神经网络PID算法,BSO改进模糊神经网络PID算法有效提高了系统的鲁棒性,同时系统对位置指令响应速度快且无超调,抗干扰能力强,具有更好的动态性能。
To improve the stability of a two-phase hybrid stepper motor and realize precise control of stepper motor position
a beetle swarm optimization (BSO) improved fuzzy neural network proportional integral derivative (PID) algorithm is proposed. Firstly
the BSO improved fuzzy neural network PID controller is designed on the basis of the mathematical model of the two-phase hybrid stepper motor
and the proper PID parameters are obtained with the BSO algorithm for iterative optimization. Then
the PID parameters are real-time regulated by the fuzzy neural network. Finally
the algorithm is simulated and verified using MATLAB software
and the step response experiments and signal following experiments are carried out on the stepper motor position closed-loop motion platform
respectively. The simulation and experimental results show that compared with the traditional PID algorithm
the BSO-PID algorithm
and the fuzzy neural network PID algorithm
the BSO improved fuzzy neural network PID algorithm effectively improves the system robustness. Meanwhile
the system responds to position commands quickly without overshooting
and has stronger anti-interference ability and better dynamic performance.
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010602201714号