Synergizing Language Models and Biogas Plant Control: A GPT-4 Approach
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This study delves into the utilization of the large language model, GPT-4, as a controller to optimize substrate feed in an agricultural anaerobic co-digestion plant. Assigned with specific objectives, including targeted methane production, GPT-4 harnesses knowledge encompassing plant parameters, substrate characteristics, and real-time process data. The model formulates recommendations for substrate feed, offering transparent rationales for its decisions. To evaluate its effectiveness, a simulation model of an agricultural anaerobic co-digestion plant based on the Anaerobic Digestion Model no. 1 is employed. Initial findings suggest that GPT-4 effectively regulates substrate feed, maintaining methane production rates near predefined targets. Crucially, the explanations provided by GPT-4 are comprehensible. The accompanying code will be made accessible for further investigation and exploration.