摘要
为提高交错并联双向DC/DC变换器的动态性能与抗干扰能力,提出一种基于模糊神经网络PID的控制方法.建立并联交错双向DC/DC变换器的小信号数学模型,得到输出电压与电感电流的传递函数;设计模糊神经网络PID控制器,应用到变换器双闭环控制的电压外环.仿真结果表明:与模糊PID控制、RBF神经网络PID控制相比,Buck模式下,模糊神经网络PID控制下的变换器输出电压达到稳态的时间为15 ms,超调量为1%,加入扰动后30 ms即可恢复稳态;Boost模式下的仿真结果与Buck模式相似,证明了模糊神经网络PID控制方法的优越性和有效性.
In order to improve the dynamic performance and anti-interference ability of interleaved parallel bidirectional DC/DC converter,a control method based on fuzzy neural network PID is proposed.The small signal mathematical model of parallel interlacing bidirectional DC/DC converter is established,and the transfer function of output voltage and inductance current is obtained.Fuzzy neural network PID controller is designed and applied to voltage outer loop of double closed loop control of converter.The simulation results show that compared with fuzzy PID control and RBF neural network PID control,under Buck mode,the output voltage of the converter under fuzzy neural network PID control takes 15 ms to reach steady state,the overshoot is 1%,and the steady state can be restored 30 ms after adding disturbance.The simulation results in Boost mode are similar to those in Buck mode,which proves the superiority and effectiveness of fuzzy neural network PID control method.
作者
任乐天
宋超
韩俊杰
金昱岐
刘德君
REN Letian;SONG Chao;HAN Junjie;JIN Yuqi;LIU Dejun(College of Electrical and Information Engineering,Beihua University,Jilin 132021,China;Engineering Training Center,Beihua University,Jilin 132021,China)
出处
《北华大学学报（自然科学版）》
CAS
2023年第5期671-677,共7页
Journal of Beihua University（Natural Science）
基金
吉林省教育厅科学技术研究项目(JJKH20210042KJ,2015148)
北华大学研究生创新计划项目(2022006)。
