A considerable amount of research within the last few decades has been focusing on controllers for switched reluctance motor drives and how they affect the torque ripple. Despite all its potentials, there are still major concerns and obstacles to overcome concerning the dependency of the magnetic characteristic of the switched reluctance motor. This work targets these concerns by proposing an initial study of the fundamentals of a drive scheme using a finite set model predictive control for a switched reluctance motor through an asymmetric bridge converter. The implementation of this scheme is the main contribution of this paper. The method uses the dynamic model of the motor to estimate the future behavior of the current for each converter state. A cost function then evaluates which switching state minimizes the current error and applies it to the motor. Some simulation results illustrate the technique. Simulation results show the good performance of the method with fast and accurate transient response.