Data Driven Systems and Control Framework for Multiway Dynamical Systems

Abstract

The use of multiway dynamical systems is expected to providemore compact generative models than the “vectorized” counterparts, to be more robust tothe small sample size problem in data driven applications, and to provide new ways formanipulating/controlling the system by retaining and exploiting the inherent structure inthe tensorial representation. A particular emphasis ofour research will be on the data driven setting and applications where first principle modelsare not available, and on developing a computationally efficient framework associated withmultiway dynamical system identification and control.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 09, 2018
Source ID
FA95501810028

Entities

People

  • Indika Rajapakse

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of Michigan

Tags

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Neural Network Machine Learning.
  • Neurological Diseases/Conditions/Disorders

Technology Areas

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