Velocity Ripple Suppression of APMSM via Iterative Learning Sliding Mode Control Considering Coil Switching

Abstract

In an annular permanent magnet synchronous motor (APMSM), a driving strategy based on alternating coil operation enables the simultaneous driving of multiple movers with a single stator module. However, coil switching and stator module splicing cause velocity ripple. This article first analyzes the factors causing velocity ripple specific to the APMSM control system. Then, a iterative learning sliding mode controller (ILSMC) algorithm is proposed and verified to be asymptotically stable using Lyapunov’s theorem. ILSMC combines the self-correction capability of iterative learning control (ILC) and the strong robustness of sliding mode control (SMC) in a parallel structure. Comparative experiments on the APMSM experimental platform demonstrate that the proposed ILSMC excels in velocity ripple suppression and velocity tracking under no-load, load, external load, and system parameter variation. Considering the APMSM operation is characterized by repetitive velocity trajectory tasks, the ILSMC with its iterative update function provides a promising approach for applying intelligent control technology in APMSM controller design.