CAJ | 학술논문

将神经元网络与模糊PID复合控制技术应用在光伏系统MPPT控制器中，解决光伏系统传统MPPT控制算法的局限性以及无法自适应外部复杂情况等诸多问题。利用离线训练后的前馈神经网络预测最大功率点电压与实际电压进行比较，作为模糊控制器的输入，通过模糊推理对PID相关参数实现最佳调整。仿真结果表明：该控制算法能增强消除系统误差能力，可获得更高的控制精度。
장신경원망락여모호PID복합공제기술응용재광복계통MPPT공제기중，해결광복계통전통MPPT공제산법적국한성이급무법자괄응외부복잡정황등제다문제。이용리선훈련후적전궤신경망락예측최대공솔점전압여실제전압진행비교，작위모호공제기적수입，통과모호추리대PID상관삼수실현최가조정。방진결과표명：해공제산법능증강소제계통오차능력，가획득경고적공제정도。
In this paper,the neuronal network and fuzzy PID composite control technology were applied in the MPPT controller of photovoltaic system,which solved the problems of the control algorithm of traditional photovolta-ic system and it cannot adapt to complex external conditions. Calculate maximum power voltage by the off-line trained feed-forward neural network,and compare it with the actual voltage. Putting the results into the vague con-troller,and adjust PID related parameters by vague illation. The simulation results showed that the control algorithm can enhance the ability of eliminating system errors and obtain higher control precision.