Model-Free Predictive Current Control of SPMSM Based on Enhanced Extended State Observer

被引:20
作者
Wu, Xuan [1 ]
Zou, Pinlong [1 ]
Huang, Sheng [1 ]
Yang, Meizhou [1 ]
Wu, Ting [1 ,2 ]
Huang, Shoudao [1 ]
Cui, Hesong [3 ]
机构
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410012, Hunan, Peoples R China
[2] Hunan First Normal Univ, Coll Elect Informat, Changsha 410205, Hunan, Peoples R China
[3] Machinery Ind Beijing Electrotech Inst Econ Res, Beijing 100070, Peoples R China
基金
美国国家科学基金会;
关键词
Model-free predictive current control (MFPCC); parameter mismatch; robustness; ultra-local model; SYNCHRONOUS MOTORS; SENSORLESS CONTROL; ELECTRICAL DRIVES; PARAMETER; PMSM; IDENTIFICATION; COMPENSATION; MACHINES; VSI;
D O I
10.1109/TIE.2023.3279526
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Conventional model-free predictive current control (MFPCC) using an extended state observer (ESO) based on ultra-local model significantly decreases the sensitivity to partial motor parameters. However, the performance and stability of ESO will be degraded in the face of amplified high-frequency (HF) perturbation caused by inductance parameter mismatch. To solve the above problem, an enhanced ESO-based MFPCC method is proposed in this article. On the basis of constructing the discrete equation of ESO, an accurate and fast calculation of inductance parameter is proposed, which is real-time convergence to the actual value by deadbeat control principle, and fed back to the lumped disturbance and current observation calculation. It effectively eliminates the effects of HF perturbation on ESO. Simultaneously, the inductance and compensated lumped disturbance obtained from ESO are provided to the MFPCC command voltage calculation module, further improving the parameter robustness of MFPCC. The stability of the proposed ESO is ensured by the design of observer gain. Experiments are carried out on 1-kW surfaced permanent magnet synchronous machines test bench. Compared with the conventional ESO-based MFPCC method, the proposed method is superior in dynamic response, steady-state performance, and parameter robustness.
引用
收藏
页码:3461 / 3471
页数:11
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