Design of a Fuzzy-Based Adaptive Gain Filter for PMSM Servo Systems With Maneuverability

In order to overcome the disadvantages of complexity and nonadaptability of the conventional Kalman filter (KF) in servo systems with maneuverability, a novel fuzzy-based adaptive gain filter (FAGF) is proposed in this article. First, based on the principle of KF, a third-order fixed gain filter model is established to realize the state observation of the permanent magnet synchronous motors 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.