Adaptive backstepping control with real-time fuzzy logic parameter selection of a field-oriented control-based permanent magnet synchronous motor driver

Abstract

This study proposes an adaptive backstepping control approach integrated with a real-time fuzzy logic parameter selection algorithm to enhance the robustness and stability of a permanent magnet synchronous motor (PMSM) controller under parametric uncertainties and external disturbances. Although backstepping control performs well under varying disturbances, it must be supported by an adaptive control algorithm to effectively handle both variable disturbances and parameter uncertainties. Moreover, because the fixed parameters of the adaptive backstepping controller limit the dynamic performance of the velocity tracking loop, this study incorporates fuzzy logic control-a soft computing algorithm capable of real-time parameter adjustment-to achieve more robust outcomes. Therefore, a fuzzy logic-based parameter selection structure is integrated into the controller for real-time operation, and its contribution to control performance is investigated. The proposed control schemes are compared with a conventional proportional-integral (PI) motor controller. All modeling and simulation studies are carried out in the MATLAB/Simulink environment.