Open AccessSensorless current model control for permanent magnet synchronous motor based on IPID with two‐dimensional cloud model online optimisation
Author(s) -
Wei Haifeng,
Tao Heng,
Duan Fuqiao,
Zhang Yi,
Li Yuanjiang,
Luo Zhihong
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.5892
Subject(s) - control theory (sociology) , computer science , robustness (evolution) , particle swarm optimization , harmonics , rotor (electric) , current loop , synchronous motor , position (finance) , current (fluid) , control engineering , engineering , algorithm , control (management) , artificial intelligence , chemistry , finance , voltage , mechanical engineering , biochemistry , electrical engineering , economics , gene
In this study, a sensorless current model control algorithm for permanent magnet synchronous motor (PMSM) is investigated based on intelligent proportion integration differentiation (IPID) with two‐dimensional cloud model online optimisation. To obtain a relatively accurate rotor position and speed estimation, in virtual γ − δ rotating coordinate system, estimation of the position and speed is performed using a current error between an actual current and the model current obtained from a current model of the motor. Simultaneously, a type of IPID with parameter dynamic real‐time self‐tuning function is designed to adjust the speed and current loop in the current model control. By introducing the chaos particle swarm optimisation (CPSO) algorithm to optimise the control parameters offline, the entire control system is in the optimised state, then the two‐dimensional cloud model online adjustment module is used to perform real‐time tuning. The experimental results show that the new control algorithm proposed can accurately estimate the real‐time rotor position and speed, which effectively avoids the influence of back EMF harmonics, and it has the robustness to motor internal parameter perturbation and external load disturbance.