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

A high-performance ripple-free dynamic torque controller for a variable-reluctance (VR) motor intended for trajectory tracking in robotic applications is designed. A modeling approach that simplifies the design of the controller is investigated. Model structure and parameter estimation techniques are presented. Different approaches to the overall torque controller design problem are discussed, and the solution adopted is illustrated. A cascade controller structure consisting of a feedforward nonlinear torque compensator, cascaded to a nonlinear flux or current closed-loop controller is considered, and optimization techniques are used for its design. Although developed for a specific commercial motor, the proposed modeling and optimization strategies can be used for other VR motors with magnetically decoupled phases, both rotating and linear. Laboratory experiments for model validation and preliminary simulation results of the overall torque control system are presented