Continuous Control Set-Model Predictive Control for Torque Control of Induction Motors in a Wide Speed Range

Abstract This paper proposes a novel continuous control set model predictive control (CCS-MPC) method for the torque control of induction motors. A systematic way to define a reference state for the given torque reference is provided. The reference state is determined according to three different operational modes to yield the highest possible efficiency. First, at low speeds, the maximum torque per ampere (MTPA) is achieved considering ohmic loss minimization. Second, the flux reference is limited by increasing the slip frequency with increase in the reference torque. Third, MTPA in field-weakening region is adopted. In proposed MPC, a cost index is defined using the derived reference state and the optimal control input is determined considering the input constraints. This control input is obtained without use of any numerical algorithm at each time step. The stability analysis of the closed-loop control system is performed. The proposed control is implemented and validated by simulation and experimental studies at steady and transient states. The results confirm that the proposed approach gives a very good dynamic performance in a wide speed range within the machine’s capability. The ripples in torque and current are reduced compared to the last referenced MPC of IM.