Design of Hierarchical, Adaptive Control Systems

Abstract

On this grant we have worked on the hierarchical, hybrid adaptive control of multi-agent systems. The research results have resulted in some spectacular new results in the following areas: (1) algorithms for hybrid control of multi-agent systems with proofs of correctness for safety properties with applications to several practical systems. (2) techniques for consistent hierarchical models of complex systems; finite bisimulation results (exhaustive) for all finitely verifiable systems. (3) neurodynamic learning for complex hybrid systems with applications to realistic rendering of human motor actions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 29, 2000
Accession Number
ADA384430

Entities

People

  • S. Shankar Sastry

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Adaptive Control Systems
  • Air Traffic
  • Autonomous Vehicles
  • Classification
  • Command And Control
  • Complex Systems
  • Computer Graphics
  • Control Systems
  • Hybrid Systems
  • Intelligent Systems
  • Learning
  • Mathematical Models
  • Military Research
  • Models
  • Multiagent Systems
  • Scientists
  • Unmanned Systems

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Neural Network Machine Learning.
  • Systems Analysis and Design