Data-Driven Modeling for Dual RetrospectIve Cost Adaptive Control

Abstract

This final report summarizes progress on AFOSR grant FA9550-18-1-0171 between April 1, 2018 and March 31, 2021. This project contributed to the various extensions of retrospective cost adaptive control (RCAC). These extensions include 1) RCAC-based PID control, and 2) data-driven retrospective cost adaptive control (DRCAC), where online system identification is used to obtain the required modeling information. Numerical studies illustrating these methods include a model scramjet, aerodynamic flutter, and missile guidance.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2021
Accession Number
AD1137002

Entities

People

  • Dennis S. Bernstein

Organizations

  • Board of Regents of the University of Michigan

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Combustors
  • Cost Models
  • Costs
  • Dead Time
  • Department Of Defense
  • Engines
  • Flow
  • Guidance
  • Hypersonic Vehicles
  • Information Operations
  • Information Systems
  • Mach Number
  • Michigan
  • Online Systems
  • Pressure Measurement
  • Scientific Research
  • Shock
  • Steady State
  • Supersonic Combustion Ramjet Engines
  • Supersonic Flow
  • Universities

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Robotics and Automation.