{"title":"Full-State Feedback Control for Grid-Connected DC/AC Converter With Enhanced Stability and Controllability","authors":"Yanjun Tian;Yilin Wang;Lianying An;Zhishuang Yue","doi":"10.1109/TIE.2024.3525100","DOIUrl":null,"url":null,"abstract":"Grid-connected dc/ac converter is facing the challenges of limited dc side controllability and resonant ac side eigenstate, and it is rooted that majority control strategies are normally PI controller-based output variables feedback control, but they neglect the system internal characteristics, resulting in limited controllability. State variables can reflect converter system internal characteristics, and state feedback control can effectively improve system performance. Hence, this article proposes a full-state feedback control strategy (FSFC) for the bidirectional the grid-connected converter with <italic>LCL filter</i>. On the ac side, the <italic>LCL</i> filter-based FSFC strategy is capable of expanding the passive damping configuration by relocating system poles to optimal damping point, which substantially suppresses the resonance peaks without sacrificing dynamic performance. On the dc side, the proposed FSFC method manages to reduce equivalent system model order and thus enhances the performance on dc side voltage regulation. The proposed bidirectional FSFC control method has been compared with existing mainstream control methods. The results show that the proposed method has better dynamic performance and robustness. Finally, the effectiveness of this method has been verified by both simulation and experimental results.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 8","pages":"8017-8027"},"PeriodicalIF":7.2000,"publicationDate":"2025-01-17","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/10845016/","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}
引用次数: 0
Abstract
Grid-connected dc/ac converter is facing the challenges of limited dc side controllability and resonant ac side eigenstate, and it is rooted that majority control strategies are normally PI controller-based output variables feedback control, but they neglect the system internal characteristics, resulting in limited controllability. State variables can reflect converter system internal characteristics, and state feedback control can effectively improve system performance. Hence, this article proposes a full-state feedback control strategy (FSFC) for the bidirectional the grid-connected converter with LCL filter. On the ac side, the LCL filter-based FSFC strategy is capable of expanding the passive damping configuration by relocating system poles to optimal damping point, which substantially suppresses the resonance peaks without sacrificing dynamic performance. On the dc side, the proposed FSFC method manages to reduce equivalent system model order and thus enhances the performance on dc side voltage regulation. The proposed bidirectional FSFC control method has been compared with existing mainstream control methods. The results show that the proposed method has better dynamic performance and robustness. Finally, the effectiveness of this method has been verified by both simulation and experimental results.
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.