Adaptive Control of Active Power Filter Using RBF Neural Network

An adaptive radial basis function (RBF) neural network control system for three-phase active power filter (APF) is proposed to eliminate the harmonics. Compensation current is generated to track command current so as to eliminate the harmonic current of non-linear load and improve the quality of power system. The asymptotical stability of the APF system can be guaranteed with the proposed adaptive neural network strategy. The parameters of neural network can be adaptively updated to achieve the desired tracking task. The simulation results demonstrate the good performance such as small current tracking error, reduced total harmonic distortion (THD), improved accuracy and strong robustness in the presence of parameters variation and nonlinear load. It is shown that adaptive RBF neural network control system for three-phase APF has better control effect than hysteresis control.