Robust adaptive fuzzy control for permanent magnet synchronous servomotor drives

A novel robust adaptive fuzzy control (RAFC) algorithm for the permanent magnet (PM) synchronous servomotor drives with uncertain nonlinearities and time-varying uncertainties is presented in this article. Takagi–Sugeno-type fuzzy logic systems are used to approximate uncertain functions. The RAFC algorithm is designed by use of the input-to-state stability (ISS) approach and small gain theorem. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, the possible controller singularity problem in some of the existing adaptive control schemes met with feedback linearization techniques can be removed and the adaptive mechanism with only one learning parameterization can be achieved. The proposed methodology is applied to design the position control of the PM synchronous servomotor drives. Simulation results show the effectiveness of the proposed control scheme. © 2005 Wiley Periodicals, Inc.