Data-Driven Fuzzy Constant Voltage Regulation of Inductive Power Transfer Systems

被引:0
|
作者
Xu, Donghui [1 ]
Tian, Engang [1 ]
Chen, Huwei [2 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai 200093, Peoples R China
[2] Jiangsu Aerosp Power Machinery & Elect Co Ltd, Taizhou 225300, Peoples R China
基金
中国国家自然科学基金;
关键词
Regulation; Circuit stability; Asymptotic stability; Voltage control; Stability criteria; Nonlinear systems; Data models; Topology; Phase modulation; PD control; Data-driven technique; output regulation; inductive power transfer (IPT) system; Takagi-Sugeno model; linear matrix inequality (LMI); MISALIGNMENT TOLERANCE; WIRELESS; OPTIMIZATION;
D O I
10.1109/TCSI.2025.3529988
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper concerns the problem of constant voltage regulation for an unknown inductive power transfer (IPT) system with phase shift modulation (PSM). Different from mainstream model-based approaches, the proposed data-driven fuzzy method not only formulates a controller solely based on input-output data, but also guarantees the stability of nonlinear inductive power transfer systems. First, a data-based closed-loop fuzzy representation is derived to parameterize the nonlinear system. Subsequently, a sufficient data-based condition is proposed to ensure the stability of the nonlinear system and the asymptotically tracking characteristic without identifying the system parameters. Finally, an experimental example is proposed to demonstrate the accuracy of the proposed method and the robustness of suggested controllers.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Data-Driven Models of Monotone Systems
    Makdesi, Anas
    Girard, Antoine
    Fribourg, Laurent
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2024, 69 (08) : 5294 - 5309
  • [22] Data-Driven Modeling of Wireless Power Transfer Systems With Slowly Time-Varying Parameters
    Chen, Fengwei
    Padilla, Arturo
    Young, Peter C.
    Garnier, Hugues
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2020, 35 (11) : 12442 - 12456
  • [23] A Data-Driven Approach of Takagi-Sugeno Fuzzy Control of Unknown Nonlinear Systems
    Zhang, Bin
    Shin, Yung C.
    APPLIED SCIENCES-BASEL, 2021, 11 (01): : 1 - 16
  • [24] Data-driven output regulation control for constrained linear systems
    Xia, Chaoyu
    Dong, Yi
    Wang, Chaoli
    Xu, Shengyuan
    SCIENCE CHINA-INFORMATION SCIENCES, 2025, 68 (03)
  • [25] Data-driven harmonic output regulation of a class of nonlinear systems
    Hu, Zhongjie
    De Persis, Claudio
    Simpson-Porco, John W.
    Tesi, Pietro
    SYSTEMS & CONTROL LETTERS, 2025, 200
  • [26] Review of Data-Driven Techniques for On-Line Static and Dynamic Security Assessment of Modern Power Systems
    De Caro, Fabrizio
    Collin, Adam John
    Giannuzzi, Giorgio Maria
    Pisani, Cosimo
    Vaccaro, Alfredo
    IEEE ACCESS, 2023, 11 : 130644 - 130673
  • [27] Data-driven model predictive control of community batteries for voltage regulation in power grids subject to EV charging
    Amani, Ali Moradi
    Sajjadi, Samaneh Sadat
    Somaweera, W. Arachchige
    Jalili, Mahdi
    Yu, Xinghuo
    ENERGY REPORTS, 2023, 9 : 236 - 244
  • [28] Data-Driven Linear-Time-Variant MPC Method for Voltage and Power Regulation in Active Distribution Networks
    Li, Siyun
    Wu, Wenchuan
    IEEE TRANSACTIONS ON SMART GRID, 2024, 15 (03) : 2625 - 2638
  • [29] A Quasi-Z-Source-Based Inductive Power Transfer System for Constant Current/Constant Voltage Charging Applications
    Castiglia, Vincenzo
    Campagna, Nicola
    Miceli, Rosario
    Viola, Fabio
    Blaabjerg, Frede
    ELECTRONICS, 2021, 10 (23)
  • [30] Distributed Data-Driven Frequency Control in Networked Microgrids via Voltage Regulation
    Tang, Zhiyuan
    Liu, Youbo
    Liu, Tingjian
    Qiu, Gao
    Liu, Junyong
    IEEE TRANSACTIONS ON SMART GRID, 2024, 15 (05) : 4393 - 4406