Parallel Model Predictive Control of Switched Reluctance Machine Without Weighting Factors

In this paper, a new model predictive control strategy is proposed, featuring a Fourier model based on switched reluctance machine (SRM), cross-selection of the optimal switching signal to drive the machine by reconstructing the torque and current error formulas, considering torque ripple and copper loss requirements, multi-objective equivalent control and elimination of the weighting factor in the cost function. Simulations and experiments of steady-state performance and dynamic performance are also conducted to verify the feasibility of the proposed control strategy.