Parallel Computation for Developing Nonlinear Control Procedures.

Abstract

Efforts since 1 October 1978 have been concerned with the application of the developed parallel optimization procedures to the design of non-linear flight control systems. Consideration has been given to the advantages to be gained from the direct use of the non-linear equations of motion and to the potential for rapid on-line optimization in response to tracked parameter changes and/or changes in the mission objectives. To date, based upon the non-linear longitudinal equations for the F-8, it has been shown that parallel optimization procedures alone can reduce the time required for optimization by at least 30% and that the direct use of the nonlinear (rather than the linearized) equations of motion does indeed improve attitude control. A study of further incorporation of parallelism into the basic utility routines such as integration and matrix manipulation has shown that the convergence time for a representative optimal control computation can be reduced by a factor of 20. Thus, it was concluded that incorporation of parallel computers might indeed permit online control computation and/or adaptation. To this effect possible architectural structures for such computers have also been studied.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1981
Accession Number
ADA107914

Entities

People

  • Howard Kaufman
  • Richard Travassos

Organizations

  • Rensselaer Polytechnic Institute

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Boundary Value Problems
  • Calculus Of Variations
  • Computational Science
  • Computations
  • Control Systems
  • Differential Equations
  • Equations Of Motion
  • Estimators
  • Kalman Filters
  • Mathematical Filters
  • Parallel Computing
  • Parallel Processing
  • Plastic Explosives
  • Systems Engineering
  • Theorems

Fields of Study

  • Physics

Readers

  • Control Systems Engineering.
  • Parallel and Distributed Computing.
  • Robotics and Automation.