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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2406.12628 |
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| _version_ | 1866929390922760192 |
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| author | Cui, Chenggang Liu, Jiaming Feng, Junkang Hui, Peifeng Ghias, Amer M. Y. M. Zhang, Chuanlin |
| author_facet | Cui, Chenggang Liu, Jiaming Feng, Junkang Hui, Peifeng Ghias, Amer M. Y. M. Zhang, Chuanlin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_12628 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Large Language Models based Multi-Agent Framework for Objective Oriented Control Design in Power Electronics Cui, Chenggang Liu, Jiaming Feng, Junkang Hui, Peifeng Ghias, Amer M. Y. M. Zhang, Chuanlin Systems and Control 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. |
| title | Large Language Models based Multi-Agent Framework for Objective Oriented Control Design in Power Electronics |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2406.12628 |