Improved Data-Driven Control Design Based on LMI and Its Applications in Lithium-Ion Batteries

Quan Yong Fan; Yucong Sun; Bin Xu

doi:10.1109/TCSII.2023.3288149

Improved Data-Driven Control Design Based on LMI and Its Applications in Lithium-Ion Batteries

Quan Yong Fan, Yucong Sun, Bin Xu

School of Automation

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

This brief focuses on the data-driven control for discrete-time systems based on linear matrix inequality (LMI) and provides its application in Lithium-Ion batteries with disturbances. First, the system's state response is collected from a noisy environment to obtain the data matrices. Then, a new definition of parameters is proposed to improve the solvability of LMIs. To enhance the control scheme's robustness against disturbances, a penalty function with an adjustable factor is introduced. The range of disturbances that can be tolerated is quantified under the control mechanism. Finally, data-driven state-of-charge tracking control for Lithium-Ion batteries is studied in the simulation. Comparisons with existing approaches show the effectiveness and superiority of the proposed method in terms of performance and disturbance tolerance.

Original language	English
Pages (from-to)	4504-4508
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
Volume	70
Issue number	12
DOIs	https://doi.org/10.1109/TCSII.2023.3288149
State	Published - 1 Dec 2023

Keywords

Data-driven control
Lithium-Ion battery
linear matrix inequality
state-of-charge tracking control

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TCSII.2023.3288149

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abstract = "This brief focuses on the data-driven control for discrete-time systems based on linear matrix inequality (LMI) and provides its application in Lithium-Ion batteries with disturbances. First, the system's state response is collected from a noisy environment to obtain the data matrices. Then, a new definition of parameters is proposed to improve the solvability of LMIs. To enhance the control scheme's robustness against disturbances, a penalty function with an adjustable factor is introduced. The range of disturbances that can be tolerated is quantified under the control mechanism. Finally, data-driven state-of-charge tracking control for Lithium-Ion batteries is studied in the simulation. Comparisons with existing approaches show the effectiveness and superiority of the proposed method in terms of performance and disturbance tolerance.",

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AB - This brief focuses on the data-driven control for discrete-time systems based on linear matrix inequality (LMI) and provides its application in Lithium-Ion batteries with disturbances. First, the system's state response is collected from a noisy environment to obtain the data matrices. Then, a new definition of parameters is proposed to improve the solvability of LMIs. To enhance the control scheme's robustness against disturbances, a penalty function with an adjustable factor is introduced. The range of disturbances that can be tolerated is quantified under the control mechanism. Finally, data-driven state-of-charge tracking control for Lithium-Ion batteries is studied in the simulation. Comparisons with existing approaches show the effectiveness and superiority of the proposed method in terms of performance and disturbance tolerance.

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Improved Data-Driven Control Design Based on LMI and Its Applications in Lithium-Ion Batteries

Abstract

Keywords

UN SDGs

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