Huiyue Zhang, Ming Li, and Ying Wang
Active power filters, sliding mode control, neural networks
In this article, an active power filter (APF) integrating sliding mode control and the radial basis function neural network (RBFNN) is proposed to track and suppress harmonic wave components generated by nonlinear loads in a power grid. The mathematical model of the APF is derived, and the sliding mode control strategy is presented. In addition, an RBFNN is proposed to approximate to the nonlinear characteristics of the plant so as to improve the controller’s performance. The simulation and experimental results validate the effectiveness of the proposed approach.
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