A Feasibility Study on Applying Large Language Model Techniques to Grey-Box Modeling for Model Predictive Control

Taehun Yeo; Jeonghun Seo; Chanhyuk Mo; Jaewan Joe

doi:10.7836/kses.2026.46.3.237

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2026 Vol.46, Issue 3 Preview Page

A Feasibility Study on Applying Large Language Model Techniques to Grey-Box Modeling for Model Predictive Control 모델기반 예측제어를 위한 Grey-box 모델링의 LLM 기법 적용 가능성 검토 연구

30 June 2026. pp. 237-250

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Abstract

This study investigates the applicability of large language model (LLM) assistance to control-oriented grey box thermal modeling for future model predictive control (MPC) applications. Three modeling methods are compared under identical measured data conditions comprising a hand-coded RC grey box, an AI-generated RC grey box, and an AI-generated ANN black box. The experiments used measured sensor data obtained at 15 min intervals from four building zones and considered the official L1-L4 information levels. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of variation of the root mean square (CVRMSE) for both one-step prediction and 24-h recursive rollout prediction. The results showed that the performance of the AI-generated RC grey box was more consistent across zones and information levels than the AI-generated ANN black box. Meanwhile, the artificial neural network (ANN) remained competitive in some cases but showed larger variability. These findings indicate that LLM assistance can support structured and reproducible grey-box workflow development without the need to replace conventional engineering modeling.

Keywords

grey-box model

large language model

artificial neural network

building thermal modeling

model predictive control

prediction accuracy

키워드

그레이박스 모델

대규모 언어모델

인공신경망

건물 열모델링

모델기반 예측제어

예측 정확도

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Information

Publisher :Korean Solar Energy Society
Publisher(Ko) :한국태양에너지학회
Journal Title :Journal of the Korean Solar Energy Society
Journal Title(Ko) :한국태양에너지학회 논문집
Volume : 46
No :3
Pages :237-250
Received Date : 2026-04-06
Revised Date : 2026-05-21
Accepted Date : 2026-05-26
DOI :https://doi.org/10.7836/kses.2026.46.3.237

Journal of the Korean Solar Energy Society ISSN:1598-6411(Print) 2508-3562(Online) 한국태양에너지학회 논문집

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