A Large Language Model based Multi-agent Framework for Goal Oriented Controller Design in Power Electronics

Power electronics, a critical component in modern power systems, face several challenges in control design, including model uncertainties, and lengthy and costly design cycles. This paper is aiming to propose a Large Language Models (LLMs) based multi-agent framework for objective-oriented control design in power electronics. The framework leverages the reasoning capabilities of LLMs and a multi-agent workflow to develop an efficient and autonomous controller design process. The LLM agent is able to understand and respond to high-level instructions in natural language, adapting its behavior based on the task’s specific requirements and constraints from a practical implementation point of view. This novel and efficient approach promises a more flexible and adaptable controller design process in power electronics that will largely facilitate the practitioners.

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Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1109/ceepe64987.2025.11034293
Citations
2
Primary Topic
Real-time simulation and control systems
Type
article
Field-Weighted Citation Impact
2.43
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article

A Large Language Model based Multi-agent Framework for Goal Oriented Controller Design in Power Electronics

Chenggang Cui, J. Liu, Amer M. Y. M. Ghias, Pengfeng Lin et al.
2 citations
Real-time simulation and control systems
2.43
article

A Large Language Model based Multi-agent Framework for Goal Oriented Controller Design in Power Electronics

Chenggang Cui, J. Liu, Amer M. Y. M. Ghias, Pengfeng Lin, Chuanlin Zhang, Peifeng Hui
article en
2 citations

Abstract

Power electronics, a critical component in modern power systems, face several challenges in control design, including model uncertainties, and lengthy and costly design cycles. This paper is aiming to propose a Large Language Models (LLMs) based multi-agent framework for objective-oriented control design in power electronics. The framework leverages the reasoning capabilities of LLMs and a multi-agent workflow to develop an efficient and autonomous controller design process. The LLM agent is able to understand and respond to high-level instructions in natural language, adapting its behavior based on the task’s specific requirements and constraints from a practical implementation point of view. This novel and efficient approach promises a more flexible and adaptable controller design process in power electronics that will largely facilitate the practitioners.

Nanyang Technological University (SG), Shanghai Jiao Tong University (CN), Shanghai University of Electric Power (CN)
Openalex Percentile: Top 11%
Real-time simulation and control systems
2.43
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