摘要
利用极端学习机(ELM)刻画复杂非线性系统的能力,以及较高的学习速度和良好的泛化性特点,将其运用于静止无功发生器的控制方案中。Matlab仿真表明,此控制方法不仅具有电流直接控制的控制精度同时还在训练时间上小于BP网络。
Using the ability of depicting the complex nonlinear systems , higher speed of learning and the good generali- zation properties to control the static vat generator. The simulation results show that the proposed control method not only has the accuracy of the direct current control, but also the training time is less than BP neural network.
出处
《电气开关》
2013年第1期63-65,共3页
Electric Switchgear
