Adaptive Neural Sliding Mode Control of Active Power Filter

作者：Fei, Juntao^*; Wang, Zhe

来源：Journal of Applied Mathematics, 2013, 2013: 341831.

DOI：10.1155/2013/341831

• NONLINEAR CONTROL
• STRATEGY
• DESIGN

A radial basis RBF) neural network adaptive sliding mode control system is developed for the current compensation control of three-phase active power filter (APF). The advantages of the adaptive control, neural network control, and sliding mode control are combined together to achieve the control task; that is, the harmonic current of nonlinear load can be eliminated and the quality of power system can be well improved. Sliding surface coordinate function and sliding mode controller are used as input and output of the RBF neural network, respectively. The neural network control parameters are online adjusted through gradient method and Lyapunov theory. Simulation results demonstrate that the adaptive RBF sliding mode control can compensate harmonic current effectively and has strong robustness to disturbance signals.

• 出版日期2013
• 单位河海大学