Fourth AFOSR Monterey Training Workshop on Computational Issues in Nonlinear Control. Topics at the Intersection of Deep Learning and Computational Nonlinear Control

Abstract

Over the past several decades there has been tremendous progress in the development of nonlinear systems and control theory. However, applications of these ideas have lagged behind because of the lack of effective computational tools for treating the ever-increasing scale and complexity of control systems, such as large-scale smart grids and swarms of unmanned aerial vehicles. On the other hand, advancements in machine learning had significant breakthroughs over the last few years in solving high dimensional and complicated nonlinear control problems that cannot otherwise be solved using conventional methodologies in control theory. The curse-of-dimensionality, for instance, is a bottleneck in nonlinear optimal control. The complexity of an approximate solution grows, in general, exponentially with the state space dimension. Similar bottlenecks exist in global or semi-global stabilization of high dimensional systems such as power systems with high-penetration of renewable energy. For the last few years, a new trend of overcoming the curse of dimensionality in nonlinear control using deep learning has been developed rapidly, resulting in many promising results. The proposed workshop will bring together leading experts and junior researchers across a variety of fields, and provide a platform for them to exchange ideas on deep learning for bottleneck problems in computational nonlinear control. The organizing committee consists of Wei Kang (Naval Postgraduate School and University of California, Santa Cruz), Arthur J. Krener (Naval Postgraduate School and University of California, Davis), and Qi Gong (University of California, Santa Cruz).

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 29, 2024
Source ID
FA95502310089

Entities

People

  • Arthur J. Krener

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of California, Davis

Tags

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Neural Network Machine Learning.
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers