Model predictive control of sensorless hybrid stepper motors in auxiliary adjuster for stereotactic frame fixation

A hybrid stepper motor (HSM) can be practically driven by open-loop control, however, it is definitely not enough for the increasing demands on precision control in wide industry applications. In this study, a practical control scheme, consisting of model predictive control (MPC) and extended Kalman filter (EKF), is presented for controlling a sensorless hybrid stepper motor (HSM). Numerical simulations and real-world experiments are conducted to show the performance and effectiveness of the proposed strategy. To extend the practical usage of the presented design, the proposed strategy has been utilized to control an auxiliary adjuster for stereotactic frame fixation system for use in the precise clinical neurosurgery operation.