神经网络在逆变器控制中的应用

针对传统的基于最优消谐波理论的逆变器 ,应用了一种全新的神经网络控制器。当系统工作时 ,由在线神经网络实时调节逆变器输出电压的大小 ;同时各功率管的开关角由另一个神经网络通过对最优 PWM最优开关角的拟合 ,直接计算出来。整个控制系统具有结构简单、反应灵敏、调压精确、输出电能质量高且全数字化的特点。

OPTIMAL PWM BASED ON REAL-TIME SOLUTION WITH NEURAL NETWORK

A novel concept of neural network based control in pulse width modulation (PWM) voltage source inverters is presented. On the one hand, the optimal switching angles are obtained in real time by the neural network based controller; on the other hand, the output voltage is adjusted to fit the expected value by neural network when input voltage or loads change. The structure of neural network is simple and easy to be realized by DSP hardware system. No large memory used for the existing optimal PWM schemes is required in the system. Theoretical analysis of the proposed so called sparse neural network is provided, and the stability of the system is proved. Under the control of neural network the error of output voltage descends sharply, and the system outputs ac voltage with high precision.