Finite-Control-Set Current Predictive Control of Linear Switched Reluctance Motors Using Multi- Parameter Dynamic Linearization Model

To enhance current control performance for linear switched reluctance motors (LSRMs), this paper proposes a finite-control-set (FCS) current predictive control method using a multi-parameter dynamic linearization model, addressing the challenges posed by the highly nonlinear and time-varying characteristics of LSRMs. Unlike conventional dynamic linearization models, the developed multi-parameter dynamic linearization current model resolves the issue where the current remains unchanged when there is no change in voltage. At each control interval, the FCS current predictive control method determines the optimal switch states using the updated predictive current model derived from the multi-parameter dynamic linearization model. The effectiveness of the proposed method is verified through both the simulation and experimental results.