Finite Set Model Predictive Control of a Dual-Motor Torque Synchronization System Fed by an Indirect Matrix Converter

Abstract

In the dual-motor torque synchronization system fed by an indirect matrix converter (IMC), a finite set model predictive control (FCS-MPC) strategy based on a standard quadratic cost function was proposed to solve the open-loop problem of the torque synchronization error in a traditional closed-loop control strategy. Through the unified modeling of a dual-motor system, the torque synchronization error as a new state variable was involved in the switching state selection of the inverter stages, and the space vector modulation method was still used in the rectifier stage. At the same time, based on the unified prediction model, the auxiliary diagonal matrix was constructed, and the weight coefficients were solved offline by using the Lyapunov stability theory to ensure the convergence of each error term in the continuous control period. The proposed FCS-MPC strategy not only solves the problem of weight coefficient setting, but also makes it possible for a multi-motor synchronization system to expand the number of motors. The simulation and experimental results verified the effectiveness and feasibility of the control strategy. In addition, the proposed FCS-MPC strategy can ensure good torque tracking performance and synchronization performance of each motor.