Large Language Models based Multi-Agent Framework for Objective Oriented Control Design in Power Electronics

TL;DR

This paper proposes a novel multi-agent framework utilizing Large Language Models to enhance the flexibility and efficiency of control design in power electronics, addressing traditional challenges like model uncertainties and lengthy development cycles.

Contribution

It introduces a new LLM-based multi-agent system for autonomous, objective-oriented control design in power electronics, improving adaptability and reducing design complexity.

Findings

Framework demonstrates improved design efficiency.

Enhanced adaptability to control objectives.

Potential for practical implementation in power systems.

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.