Chebyshev Fuzzy Neural Finite Time Strategy Using Extended Kalman Filter

To eliminate harmonics generated by power electronic devices, a nonsingular fast terminal sliding mode control (NFTSMC) strategy using extended Kalman filter based self-constructed Chebyshev fuzzy neural network (EKFSCCFNN) is put forward to realize the compensation to harmonic current for an active power filter (APF) with unmodeled dynamics and unknown disturbances. A Chebyshev fuzzy neural network integrated with extended Kalman filter algorithm and self-constructed algorithm is adopted to estimate the model and disturbances of the system which simultaneously possesses the characteristic of global best uniform approximation, updating the number of fuzzification rules and neurons in real-time and converging with a faster speed. A NFTSMC scheme is employed to avoid singular phenomenon in the control law with finite convergence time, thus enhancing the feasibility of the control strategy in practical engineering. Simulation and experimental studies sufficiently demonstrate the effectiveness of the proposed control scheme, showing better steady-state and dynamic performance compared with other existing methods.