From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems

Abstract

Large scale dynamical systems (e.g. many nonlinear coupled differential equations) can often be summarized in terms of only a few state variables (a few equations), a trait that reduces complexity and facilitates exploration of behavioral aspects of otherwise intractable models. High model dimensionality and complexity makes symbolic, penÐandÐpaper model reduction tedious and impractical, a difficulty addressed by recently developed frameworks that computerize reduction. Symbolic work has the benefit, however, of identifying both reduced state variables andÉ

Document Details

Document Type
DoD Grant Award
Publication Date
Oct 16, 2018
Source ID
W911NF1710306

Entities

People

  • Igor Mezić

Organizations

  • Army Contracting Command
  • United States Army
  • University of California, Santa Barbara

Tags

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms