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This video tutorial introduces data-driven regression for model predictive control, focusing on system identification to find best-fit models using regression techniques like DMD and Koopman. The sparse identification of nonlinear dynamics with control is a framework to obtain fully nonlinear models directly from data for use in control optimization. The Sindhi method involves using measurement data of a nonlinear dynamical system to form relationships between variables and identify models for control.
