Xiaodong Sun;Zhihui Huang;Zebin Yang;Gang Lei;Teng Li
{"title":"改进无模型预测电流控制抑制变频调速系统非线性和参数时变","authors":"Xiaodong Sun;Zhihui Huang;Zebin Yang;Gang Lei;Teng Li","doi":"10.1109/TIE.2025.3552258","DOIUrl":null,"url":null,"abstract":"To improve the control performance of permanent magnet synchronous motor (PMSM) drive systems, an improved model-free predictive current control based on extended state observer (ESO) with voltage source inverter (VSI) nonlinearity compensation is proposed. First, an improved model-free predictive current control (MFPCC) based on the ESO of PMSM drives is introduced, which does not require motor parameters and needs less tuning work. Then, a voltage source inverter nonlinearity compensation method is proposed to reduce the current distortion resulting from the added dead time in the three-phase bridge voltage source inverter. The approximate parameters are obtained through adjusting in the simulation, and then applied to the experiment for further fine-tuning. The model-free control based on ESO and voltage source inverter (VSI) nonlinearity compensation are combined to compensate for their respective shortcomings, achieving the suppression of periodic and aperiodic disturbances in the system. Finally, the experimental results prove its robustness to both periodic and aperiodic disturbances.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 10","pages":"9866-9875"},"PeriodicalIF":7.2000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved Model-Free Predictive Current Control for Suppressing Inverter Nonlinearity and Parametric Time-Varying of PMSM Drive Systems\",\"authors\":\"Xiaodong Sun;Zhihui Huang;Zebin Yang;Gang Lei;Teng Li\",\"doi\":\"10.1109/TIE.2025.3552258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To improve the control performance of permanent magnet synchronous motor (PMSM) drive systems, an improved model-free predictive current control based on extended state observer (ESO) with voltage source inverter (VSI) nonlinearity compensation is proposed. First, an improved model-free predictive current control (MFPCC) based on the ESO of PMSM drives is introduced, which does not require motor parameters and needs less tuning work. Then, a voltage source inverter nonlinearity compensation method is proposed to reduce the current distortion resulting from the added dead time in the three-phase bridge voltage source inverter. The approximate parameters are obtained through adjusting in the simulation, and then applied to the experiment for further fine-tuning. The model-free control based on ESO and voltage source inverter (VSI) nonlinearity compensation are combined to compensate for their respective shortcomings, achieving the suppression of periodic and aperiodic disturbances in the system. Finally, the experimental results prove its robustness to both periodic and aperiodic disturbances.\",\"PeriodicalId\":13402,\"journal\":{\"name\":\"IEEE Transactions on Industrial Electronics\",\"volume\":\"72 10\",\"pages\":\"9866-9875\"},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2025-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Industrial Electronics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10944655/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10944655/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Improved Model-Free Predictive Current Control for Suppressing Inverter Nonlinearity and Parametric Time-Varying of PMSM Drive Systems
To improve the control performance of permanent magnet synchronous motor (PMSM) drive systems, an improved model-free predictive current control based on extended state observer (ESO) with voltage source inverter (VSI) nonlinearity compensation is proposed. First, an improved model-free predictive current control (MFPCC) based on the ESO of PMSM drives is introduced, which does not require motor parameters and needs less tuning work. Then, a voltage source inverter nonlinearity compensation method is proposed to reduce the current distortion resulting from the added dead time in the three-phase bridge voltage source inverter. The approximate parameters are obtained through adjusting in the simulation, and then applied to the experiment for further fine-tuning. The model-free control based on ESO and voltage source inverter (VSI) nonlinearity compensation are combined to compensate for their respective shortcomings, achieving the suppression of periodic and aperiodic disturbances in the system. Finally, the experimental results prove its robustness to both periodic and aperiodic disturbances.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.