一种基于模糊神经网络的PI双闭环SPWM逆变器控制方法

A PI Double Closed-loop SPWM Inverter Control Method Based on Fuzzy Neural Network

提出了一种基于模糊神经网络的PI双闭环SPWM逆变器控制方法。该方法在分析PI控制器比例系数和积分系数的对控制效果影响的基础上,设计了模糊神经网控制器,自动调整PI控制器参数,同时引入双闭环控制,进一步控制输出信号。单相逆变电源系统仿真实验表明,与模糊自适应PI双闭环控制相比,采用基于模糊神经网络PI双闭环控制的逆变电源系统,具有更低的电压THD值、更好的稳态和动态性能。

A new dual closed-loop SPWM inverter control method based on fuzzy neural network is proposed in this paper.In this method,the fuzzy neural network controller is designed for automatically adjust the parameters of PI controller by analyzing the effect of PI controller proportion coefficient and integral coefficient,the double closed-loop control is introduced at the same time to control the output signal further.The performance of the proposed method is compared with fuzzy adaptive PI double closed-loop control.Single phase inverter power supply system simulation experiments show that,inverter power supply system controlled by PI double-closed loop control based on fuzzy neural network,has a lower voltage THD value,better steady-state and dynamic performance.