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It includes applications such as control gain selection for dynamic systems and constrained resource extraction using direct methods.\n\u003cimg src=\"https://github.com/user-attachments/assets/698eded0-4e20-43fd-943d-6fc0bc6d64a7\" width=\"600\" height=\"300\"\u003e\n\n## Simulation-Based Optimal Control – SYSE 511\n\nThis repository contains MATLAB implementations and LaTeX writeups for two optimal control tasks:  \n1. **LQR Design** – Includes gain tuning, pole analysis, rise-time targeting, and finite-horizon Riccati integration (Parts a–d).  \n2. **Nonlinear Resource Extraction** – Solves a constrained optimal control problem using direct optimization with control discretization and state simulation.\n\n---\n\n### Instructions\n\n1. Run all MATLAB scripts in order to generate the required plots (`.pdf`).  \n2. Upload the provided LaTeX file and the exported plots into Overleaf.  \n3. Compile the LaTeX document to produce the final report.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fziraddingulumjanly%2Fsimulation-based-optimal-control-methods","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fziraddingulumjanly%2Fsimulation-based-optimal-control-methods","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fziraddingulumjanly%2Fsimulation-based-optimal-control-methods/lists"}