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Improving process systems engineering with specialized multi-agent large language models
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DOI：10.1016/j.ceja.2026.101141.png)
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Abstract
En 中文
• Specialized multi-agent LLMs were evaluated on chemical engineering tasks. • LLMs were applied to develop solutions for sensing, modeling, and nonlinear control. • ATR-FTIR calibration models achieve R2>0.97 with automated feature selection. • Population balance models are iteratively refined and recover correct equilibrium behavior. • NMPC formulations reach set-points with computation times below 20 s per control move.
Keywords:
Process systems engineering
Large language models
Smart industry
Dynamic modeling
Process control
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