Model Selection for the Multiple Model Adaptive Algorithm for In-Flight Simulation.

Abstract

This thesis extends the research accomplished by Capt Pineiro and Lt Berens in the area of adaptive algorithm implementation. Specifically, this thesis explores the performance characteristics of the multiple model estimation algorithm and how they influence the selection of aircraft models to allow the parameter adaptive control system to maintain tracking performance over a portion of the flight envelope. The aircraft dynamic equations used are those of the AFTI/F-16 and the control law design is based on the method developed by Professor Porter. After selecting a set of aircraft models that results in the best overall system response, the effect of adjusting the control law gains on the performance of the multiple model estimation algorithm is evaluated. By assuming that all states are accessible, sensor noise is then added to each of the longitudinal states to study how noise impacts model selection. A set of models that produces acceptable tracking performance over the desired flight envelope and the most immunity to sensor noise is then selected.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1987
Accession Number
ADA189715

Entities

People

  • James R. Mathes Jr

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Adaptive Control Systems
  • Adaptive Systems
  • Aircraft Models
  • Aircrafts
  • Algorithms
  • Closed Loop Systems
  • Computational Science
  • Control Surfaces
  • Control Systems
  • Differential Equations
  • Equations
  • Fighter Aircraft
  • Flight Simulations
  • Flight Simulators
  • Mathematical Filters
  • Plastic Explosives
  • Simulators

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerodynamics/Aeronautics.