simplified and accurate predictive control method in mono-inverter dual-parallel permanent magnet synchronous motors

Mono-inverter dual parallel (midp) motors in transportation systems are the most effective method to manage energy consumption and reduce the volume, weight, and cost of electric motor drives. unbalancing the load torques and changing the speed in unequal loading are the main problems in these systems. hence, the latest methods of optimal control such as model predictive control (mpc) have been proposed. however, these methods do not lead to accurate control of midp systems because the cost function is evaluated by the limited number of control signals or solved online after a long time-consuming. this paper deals with designing the current and speed controllers of the midp system through an effective mpc method in order to reduce the computing time of the control signals and improve the motor performance in any situation. pontryagin’s principle and the lagrange method are used in designing the current and speed controllers respectively. these controllers constantly generate control signals as linearparametric functions through the offline solving of the quadratic-linear cost function. after driving and simplifying the mathematical equations, the proposed method simulates. the simulation results of the proposed method are compared with the known finite control set- model predictive control (fcs-mpc) method in the midp motors. these results validate the prompt and accurate performance of the proposed controllers in transient and steady states.