Dichotomy Solution Based Model Predictive Control for Permanent Magnet Linear Synchronous Motors

Dichotomy solution-based model predictive control (DS-MPC) for permanent magnet linear synchronous motors (PMLSM) is proposed in this paper. The conventional finite control set model predictive control (FCS-MPC) can be combined with a pulse width modulation (PWM) modulator due to an effective cost function optimization algorithm which is from the idea of dichotomy. In the algorithm, all the voltage vectors in the constrained vector plane are dynamically selected and calculated through iteration. The proposed DS-MPC for PMLSM not only keeps the same dynamic transient performance as FCS-MPC but also greatly decreases the thrust force ripple in steady state. Meanwhile, in order to enhance the robustness of PMLSM drive systems, DS-MPC is combined with a sensorless control algorithm based on model reference adaptive system (MRAS). The proper designed MRAS can easily obtain the positon and speed information based on DS-MPC. Simulation results illustrate that DS-MPC together with MRAS has an attractive performance for PMLSM drives.