System Identification: Full-State Models with Control

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This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and the sparse identification of nonlinear dynamics (SINDy).

This video was produced at the University of Washington
  1. Steve Brunton
  2. Control theory
  3. Machine learning
  4. Data science
  5. Dynamical systems
  6. Machine learning control
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