High-Precision Tracking Control of a Segmented Stator Permanent Magnet Linear Synchronous Motor

Permanent magnet linear synchronous motors (PMLSMs) are widely used in modern industrial applications, especially in industrial transportation, processing, and manufacturing processes, where high-precision position tracking is vital. By employing a segmented stator design with curvilinear segments, one can achieve complex PMLSM geometries. However, this innovative design introduces challenges in control strategies due to mounting and manufacturing tolerances during final assembly at the customer’s site. This article introduces an iterative learning-based high-precision position tracking control strategy to overcome these challenges. Our approach features a subordinate optimal force controller based on a magnetic equivalent circuit model, which adeptly handles nonlinear effects, such as magnetic saturation and cogging force. Calculating optimal currents ensures precise tractive force tracking and minimize ohmic losses, thereby increasing motor efficiency. We implement a two-degree-of-freedom position control strategy that surpasses the performance of traditional field-oriented control when combined with the optimal force controller. Despite this, larger position-tracking errors can occur during segment transitions. Accurately modeling these transitions is impractical due to the inherent errors from mounting and manufacturing tolerances. Therefore, we incorporate an iterative learning control strategy trained on the final setup to achieve exceptional position tracking across the entire curvilinear PMLSM. Experimental results from our test bench reveal remarkable accuracies within 20 $\mu$m, demonstrating the method’s robustness against manufacturing tolerances.