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Explore optimal control problem-solving in Julia through this 38-minute conference talk from JuliaCon Local Paris 2025. Learn how SciML's unified interface addresses the fragmented landscape of optimal control software across diverse applications from aerospace engineering to chemical processes. Discover how ModelingToolkit serves as a frontend that can target multiple backend solver methods used across various domains. Examine new solvers built from adaptive BVP (Boundary Value Problem) solvers that significantly outperform standard NLP (Nonlinear Programming) formulations. Gain insights into the latest developments in Julia's scientific machine learning ecosystem and understand how this unified approach can streamline optimal control workflows across different engineering and scientific applications.
