PMSM Sensorless Control Based on Moving Horizon Estimation and Parameter Self-Adaptation

被引:0
作者
Chen, Aoran [1 ]
Chen, Wenbo [2 ]
Wan, Heng [1 ]
机构
[1] Shanghai Inst Technol, Sch Railway Transportat, Shanghai 201418, Peoples R China
[2] Shanghai Inst Technol, Sch Mat Sci & Engn, Shanghai 201418, Peoples R China
关键词
moving horizon estimation; model reference adaptive system; permanent magnet synchronous motor; sensorless control; STATE ESTIMATION; DRIVE; STABILITY; SCHEME;
D O I
10.3390/electronics13132444
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The field of sensorless control of permanent magnet synchronous motor (PMSM) systems has been the subject of extensive research. The accuracy of sensorless controllers depends on the precise estimation of PMSM state quantities, including rotational speed and rotor position. In order to enhance state estimation accuracy, this paper proposes a moving horizon estimator that can be utilized in the sensorless control system of PMSM. Considering the parameter variations observed in PMSM, a nonlinear mathematical model of PMSM is established. A model reference adaptive system (MRAS) is employed to identify parameters such as resistance, inductance, and magnetic chain in real time. This approach can mitigate the impact of parameter fluctuations. Moving horizon estimation (MHE) is an estimation method based on optimization that can directly handle nonlinear system models. In order to eliminate the influence of external interference and improve the robustness of state estimation, a method based on MHE has been designed for PMSM, and a sensorless observer has been established. Considering the traditional MHE with large computation and high memory occupation, the calculation of MHE is optimized by utilizing a Hessian matrix and gradient vector. The speed and position of the PMSM are estimated within constraints during a single-step iteration. The results of the simulation demonstrate that in comparison to the traditional control structure, the estimation error of rotational speed and rotor position can be reduced by utilizing the proposed method. A more accurate estimation can be achieved with good adaptability and computational speed, which can enhance the robustness of the control system of PMSM.
引用
收藏
页数:23
相关论文
共 30 条
[1]   Nonlinear Model Predictive Control of Shipboard Boom Cranes Based on Moving Horizon State Estimation [J].
Cao, Yuchi ;
Li, Tieshan ;
Hao, Liying .
JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 11 (01)
[2]   EKF-based fault detection and isolation for PMSM inverter [J].
Dan, Luo .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 52
[3]   Speed-sensorless Predictive Current Controlled PMSM Drive With Adaptive Filtering-based MRAS Speed Estimators [J].
Demir, Ridvan .
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2023, 21 (08) :2577-2586
[4]   Output feedback receding horizon regulation via moving horizon estimation and model predictive control [J].
Fang, Yizhou ;
Armaou, Antonios .
JOURNAL OF PROCESS CONTROL, 2018, 69 :114-127
[5]   Improved dq-Axes Model of PMSM Considering Airgap Flux Harmonics and Saturation [J].
Fasil, M. ;
Antaloae, C. ;
Mijatovic, N. ;
Jensen, B. B. ;
Holboll, J. .
IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, 2016, 26 (04)
[6]   Fault Diagnosis Method of Six-Phase Permanent Magnet Synchronous Motor Based on Vector Space Decoupling [J].
Gao, Hanying ;
Guo, Jie ;
Hou, Zengquan ;
Zhang, Bangping ;
Dong, Yao .
ELECTRONICS, 2022, 11 (08)
[7]  
Hashemian N, 2015, P AMER CONTR CONF, P3379, DOI 10.1109/ACC.2015.7171854
[8]   Current-Based Open-Circuit Fault Diagnosis for PMSM Drives With Model Predictive Control [J].
Huang, Wentao ;
Du, Jiachen ;
Hua, Wei ;
Lu, Wenzhou ;
Bi, Kaitao ;
Zhu, Yixin ;
Fan, Qigao .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2021, 36 (09) :10695-10704
[9]   Dynamic scaling and observer design with application to adaptive control [J].
Karagiannis, Dimitrios ;
Sassano, Mario ;
Astolfi, Alessandro .
AUTOMATICA, 2009, 45 (12) :2883-2889
[10]   Sensorless PMSM Drive Based on Stator Feedforward Voltage Estimation Improved With MRAS Multiparameter Estimation [J].
Kivanc, Omer Cihan ;
Ozturk, Salih Baris .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2018, 23 (03) :1326-1337