Abstract
In order to overcome the disadvantages of complexity and non-adaptability of the conventional Kalman filter (KF) in servo systems with maneuverability, a novel fuzzy-based adaptive gain filter (FAGF) is proposed in this paper. Firstly, based on the principle of KF, a third-order fixed gain filter (FGF) model is established to realize the state observation of the PMSM servo system. Then, the influence of filter gain on the observation performance of a time-varying system is analyzed by deriving the covariance matrices of the observed states. On this basis, an adjustable gain is designed by fuzzy logic to replace the fixed gain of the conventional observer. The algorithm can adaptively balance the fast and smooth performance of the observer according to the maneuvering conditions of the system. Finally, the superiority of the proposed FAGF is verified by both simulations and experiments.
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.
