Switched Reluctance Linear Motor Force Ripple Suppression Based on Fixed Frequency Implicit Generalized Predictive Self-Correction Controller

An implicit generalized predictive self-correction controller (IGPC) is proposed in this paper to suppress the force ripple of switched reluctance linear motors (SRLMs). Due to its good robustness and rolling optimization features, the dynamic matrix controller (DMC), a kind of multi-step model predictive controller, is considered an effective method to suppress the force ripple of SRLMs. However, because DMC uses a fixed predictive model, it has high requirements for the accuracy of the predictive model, and the non-linear SRLMs make it difficult to adapt to different loads. To ease this problem, the IGPC proposed in this paper adopts a more flexible predictive model and improves the generalized predictive controller (GPC) to avoid solving the Diophantine equation online, which can adapt to different loads and reduce the system's burden. Besides, the proposed IGPC reduces the computational burden during matrix operations compared to DMC. In the simulation and experimental test based on a 100W 6/4 double-sided SRLM (DSRLM), the proposed IGPC is compared with DMC, and the force distribution function (FDF) adopts the current hysteresis, the results show that the proposed IGPC a better force ripple suppressing performance and has better load capacity compared with DMC.