Abstract
Aiming at the difficulties in modeling the active power filter (APF) system and the susceptibility to parameter perturbation and external disturbance, this article proposes a new adaptive sliding mode controller with using a nonlinear extended state observer (NESO) based on an interval type-2 fuzzy neural network (IT2FNN) structure. The IT2FNN is designed to estimate the unknown control coefficient, so that the NESO can estimate the state of the system and the total disturbance including the unmodeled dynamics and external disturbances, and then perform feedforward compensation to achieve active disturbance rejection. Simulation and experimental results show that the proposed control strategy is effective in the harmonic suppression of the APF system and has better steady-state and dynamic performance compared with the existing methods.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
