{"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/lgr-mpc-a-user-friendly-software-based-on","title":"LGR-MPC: A user-friendly software based on Legendre-Gauss-Radau pseudo spectral method for solving Model Predictive Control problems","arxiv_id":"2310.15960","date":"2023-10-24","proceeding":null,"authors":["Saeid Bayat","James T. Allison"],"abstract":"Active components, such as actuators, constitute a fundamental aspect of engineering systems, affording the freedom to shape system behavior as desired. However, this capability necessitates energy consumption, primarily in the form of electricity. Thus, a trade-off emerges between energy usage and desired outcomes. While open-loop optimal control methods strive for efficiency, practical implementation is hampered by disturbances and model discrepancies, underscoring the need for closed-loop controllers. The Proportional- Integral-Derivative (PID) controller is widely favored in industry due to its simplicity, despite sub-optimal responses in many cases. To bridge this gap, Model Predictive Control (MPC) offers a solution, yet its complexity limits its broad applicability. This paper introduces user-friendly Python-based MPC software, enabling easy access to MPC. The effectiveness of this software is demonstrated through multiple examples, including those with a known analytical solution.","url_abs":"https://arxiv.org/abs/2310.15960v1","url_pdf":"https://arxiv.org/pdf/2310.15960v1.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":"lgr-mpc-a-user-friendly-software-based-on","repo_url":"https://github.com/saeidb71/a-user-friendly-software-based-on-legendre-gauss-radau-pseudo-spectral-method-in-python-to-solve-mpc","is_official":1,"mentioned_in_paper":1,"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":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}