Open AccessPredictive torque control of SMPMSM drive system based on extended control set and double gradient descent method
Author(s) -
Qian Wang,
Hongmei Li,
Liguo Yang,
Wang Xl,
Wanjia Ye
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1754/1/012231
Subject(s) - control theory (sociology) , torque , model predictive control , inverter , computation , weighting , direct torque control , computer science , gradient descent , voltage , voltage reference , engineering , control (management) , induction motor , algorithm , physics , artificial intelligence , acoustics , artificial neural network , electrical engineering , thermodynamics
Model predictive torque control (MPTC) has become an effective control method for the permanent magnet synchronous machine (PMSM) drive system in recent years. However, large torque and flux ripples due to the limited numbers of inverter voltage vector deteriorate the steady-state performance. In this paper, a novel model predictive torque control based on extended control set (ECS-MPTC) is proposed. First, an innovative extended control set is generated by the proposed partition method of quasi longitude and latitude lines, in which, many virtual voltage vectors are generated. Then, based on the characteristic of cost function without weighting factor, the optimal inverter voltage vector can be selected quickly by using the double gradient descent methods, and the invalid enumeration can be avoided. Thus, the computation burden can be kept in a low level. Finally, the simulation results of conventional MPTC and proposed ECS-MPTC validate that the proposed control can achieve excellent steady-state performance of PMSM drive system and low computation burden simultaneously.