An Advanced Learning-Based Linear Quadratic Regulator For Proton Exchange Membrane Fuel Cell in DC Microgrids

Research output: Chapter in Book/Conference paperConference paperpeer-review

Abstract

An advanced learning-based linear quadratic regulator (LQR) is proposed to enhance the output voltage control performance of proton exchange membrane fuel cell (PEMFC) in DC microgrids. Compared with the commonly used methods, such as the PI control and model predictive control (MPC). The proposed control method not only produces better tracking performances, but also overcomes the problem of model dependence. The superiority of proposed method under system parameter variations is verified by simulation results.

Original languageEnglish
Title of host publicationProceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023
EditorsWenjian Cai, Guilin Yang, Jun Qiu, Tingting Gao, Lijun Jiang, Tianjiang Zheng, Xinli Wang
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages263-268
Number of pages6
ISBN (Electronic)9798350312201
DOIs
Publication statusPublished - 11 Sept 2023
Event18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023 - Ningbo, China
Duration: 18 Aug 202322 Aug 2023

Publication series

NameProceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

Conference

Conference18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023
Country/TerritoryChina
CityNingbo
Period18/08/2322/08/23

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