Direct Reduced Order Mixed H2/H infinity Control for the Short Take-Off and Landing/Maneuver Technology Demonstrator (STOL/MTD)

Abstract

One of the conclusions from the STOL/MTD program was the need for a multivariable method of designing controllers of low order. This research investigated that problem by studying reduced order mixed H-two/H-infinity control theory applied to the STOL Landing configuration which employs both thrust vectoring and the use of a canard. Model matching techniques were used to obtain responses that met handling qualities criteria and reduced pilot workload by decoupling pitch rate and velocity commands. The time responses were found through nonlinear simulation and showed that the full order designs did match the ideal models very well and had good noise and wind rejection. Singular value analysis showed that the commands were decoupled very well. The reduced order method was mixed H-two/H-infinity optimization. A fourth order controller that had good performance was found by using a performance constraint, and a fourth order controller that provided good margins was found using a robustness constraint. A third order controller was also found with a performance constraint. Recommendations for finding a low order controller, with good performance and robustness are given.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1994
Accession Number
ADA278675

Entities

People

  • William C. Reigelsperger Jr.

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aeronautical Engineering
  • Aircrafts
  • Bandwidth
  • Closed Loop Systems
  • Compensators
  • Computational Science
  • Control Systems
  • Control Systems Engineering
  • Decoupling
  • Digital Information
  • Dynamics
  • Equations
  • Frequency Response
  • Measurement
  • Multiple Input Multiple Output
  • Simulations
  • Standards

Readers

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