Adaptive fuzzy-neural control of active power filter using nonsingular terminal sliding mode controller

An adaptive fuzzy-neural-network control using nonsingular terminal sliding mode control (AFNNCNTSMC) is proposed for active power filter (APF) to attenuate the effect of unknown disturbances and parameter perturbations. Firstly, the dynamic model for APF is build in which both the system parameter variations and external disturbance are considered. Then a nonsingular terminal sliding mode control based on backstepping (NTSMCB) approach is presented for current tracking control system to solve singularity point problem and realize the fast and finite time convergence. Moreover, AFNNCNTSMC is designed to relax the requirement of the prior knowledge of system parameters to improve the robustness of NTSMCB. Adaptive fuzzy-neural-network (AFNN) framework is designed to mimic the NTSMCB, where the parameters are adjusted online by the adaptive law. Simulation studies in the MATLAB/SimPower Systems Toolbox demonstrate that the proposed control methods exhibit excellent performance in both steady state and transient operation compared to traditional sliding mode control.