Fuzzy Multiple Hidden Layer Neural Sliding Mode Control of Active Power Filter With Multiple Feedback Loop

A fuzzy multiple hidden layer neural sliding mode control with multiple feedback loop (FMHLNSMCMFL) is proposed for a single-phase active power filter (APF), where a sliding mode controller is designed to make the current tracking error converge to zero and a new neural network with multiple feedback loops is introduced to approximate unknown dynamics. At the same time, the fuzzy neural network can eliminate chattering, improve the control accuracy and reduce the current distortion rate of APF. Moreover, the proposed double feedback fuzzy double hidden layer recurrent neural network is the weighted sum of fuzzy network and double hidden layer network and has strong global learning ability. The adaptive parameters obtained by Lyapunov function can ensure the asymptotic stability of the system. Simulation and hardware experiments verify the introduced FMHLNSMCMFL scheme is a viable control solution for the APF.

Automated summary

A new fuzzy multiple hidden layer neural sliding mode control with multiple feedback loop is proposed for single-phase active power filter, which introduces a neural network with multiple feedback loops to approximate unknown dynamics, improving control performance and reducing current distortion rate.