Neural network based adaptive fuzzy logic excitation controller
Neural network based adaptive fuzzy logic excitation controller
复制标题
基于神经网络的自适应模糊逻辑励磁控制器
DOI：
10.1109/icpst.2000.900062
复制
发表时间：
2000
期刊：
影响因子：
--
通讯作者：
Y. Tsutsumi
中科院分区：
文献类型：
--
作者：
T. Hiyama;Y. Tsutsumi
为了提高电力系统的整体稳定性，提出了一种基于人工神经网络的模糊逻辑励磁控制系统。所提出的控制器由一个单一的控制回路的电压和阻尼控制。控制器的输入为机端电压信号和真实的功率输出信号，输出为励磁控制信号，励磁控制信号反馈到晶闸管励磁系统。所提出的控制器显示出高度改善的控制性能的电压调节和阻尼振荡。通过在模糊逻辑励磁控制系统中加入基于人工神经网络的真实的时间整定模块，进一步提高了系统的性能。
An artificial neural network based fuzzy logic excitation control system has been proposed to enhance the overall stability of electric power systems. The proposed controller consists of a single control loop for both the voltage and the damping control. The inputs to the controller are the terminal voltage signal and the real power output signal, and the output is the excitation control signal which is fed back to the thyristor excitation system. The proposed controller shows highly improved control performance for both the voltage regulation and the damping of oscillations. Further improvement has been achieved by the addition of the artificial neural network based real time tuning block to the associated fuzzy logic excitation control system.