静止无功发生器递归神经网络自适应控制

ADAPTIVE CONTROL OF ASVG BY USING DIAGONAL RECURRENT NEURAL NETWORK

构造了新型静止无功发生器 (ASVG)递归神经网络自适应控制系统 ,该系统由递归网络辨识器及神经网络控制器构成 ,所构造的系统可以实现 ASVG的非线性自适应控制。仿真实验表明 ,该控制系统具有良好的控制品质、鲁棒性及泛化能力 ,是一种较为通用的电力系统控制模型。

The adaptive control system of ASVG by using diagonal recurrent neural network (DRNN) is proposed.Containing two neural networks that are recurrent neural network identifier and neural network controller, the proposedcontrol system can realize nonlinear adaptive control of ASVG. Simulation results show that the system has good controlcharacter, robustness and extending ability. and is a general power system control model.