{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/carbon-neutral-greenhouse-economic-model","title":"Carbon Neutral Greenhouse: Economic Model Predictive Control Framework for Education","arxiv_id":"2410.23793","date":"2024-10-31","proceeding":null,"authors":["Marek Wadinger","Rastislav Fáber","Erika Pavlovičová","Radoslav Paulen"],"abstract":"This paper presents a comprehensive framework aimed at enhancing education in modeling, optimal control, and nonlinear Model Predictive Control~(MPC) through a practical greenhouse climate control model. The framework includes a detailed mathematical model of lettuce growth and greenhouse, which are influenced by real-time external weather conditions obtained via an application programming interface~(API). Using this data, the MPC-based approach dynamically adjusts greenhouse conditions, optimizing plant growth and energy consumption and minimizing the social cost of CO\\textsubscript{2}. The presented results demonstrate the effectiveness of this approach in balancing energy use with crop yield and reducing CO\\textsubscript{2} emissions, contributing to economic efficiency and environmental sustainability. Besides optimizing lettuce production, the framework also provides a valuable resource for making control systems education more engaging and effective. The main aim is to provide students with a hands-on platform to understand the principles of modeling, the complexity of MPC and the trade-offs between profitability and sustainability in agricultural systems. This framework provides students with hands-on experience, helping them to understand the control theory better, connecting it to the practical implementation, and developing their problem-solving skills. The framework can be accessed at \\url{ecompc4greenhouse.streamlit.app}.","url_abs":"https://arxiv.org/abs/2410.23793v1","url_pdf":"https://arxiv.org/pdf/2410.23793v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"carbon-neutral-greenhouse-economic-model","repo_url":"https://github.com/MarekWadinger/ecompc-greenhouse-platform","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"model-predictive-control","task_name":"Model Predictive Control"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}