Modeling and control strategies for a variable reluctance direct-drive motor

In industrial automation and robotic applications, direct-drive motors represent a suitable solution to friction and backlash problems typical of mechanical reduction gears. Vari- able reluctance (VR) motors are well suited for direct-drive implementation but, because of the strongly nonlinear elec- tromechanical characteristics, these motors are traditionally designed as stepper motors. The main aim of the work described in the paper is the design of a high-performance ripple-free dynamic torque controller for a VR motor, idtended for trajectory tracking in robotic applica- tions. An original modeling approach is investigated in order to simplify the design of the high-performance torque controller. Model structure and parameter estimation techniques are pre- sented. Different approaches to the overall torque controller design problein are also discussed and the solution adopted is illustrated. A cascade controller structure is considered. It con- sists of a feedforward nonlinear torque compensator, cascaded to a nonlinear flux or current closed-loop controller. The feed- forward compensator is carefully considered and optimization techniques are used for its design. Two optimization criteria are proposed: the first minimizes copper losses, whereas the second minimizes the maximum value of the motor-feeding voltage. Although developed for a specific commercial motor, the pro- posed modeling and optimization strategies can be used for other VR motors with magnetically decoupled phases, both ro- tating and lidear. Laboratory experiments for model validation and preliminary simulation results of the overall torque control system are presented.