Adaptive Control of Helicopter Vibrations Via the Impulse Response Method

Abstract

An adaptive blade control algorithm for helicopter vibration reduction is developed as an application of an impulse response control method. The method is based on an impulse response formulation which is applicable to any linear system with periodic dynamics. In the investigation of adaptive helicopter vibration control presented, a vertical-axis-only plant is simulated by a model composed of an impulse response matrix and an uncontrolled vibration vector. The adaptive control is implemented by a regulator composed of an estimator and a controller. The model parameters are identified by either Kalman or batch weighted least squares (WLS) filtering in either global or local form. The resulting estimates are used in an optimal control law obtained by the minimization of a constrained, single-step, quadratic performance function. Four control laws are derived: global certainty-equivalent, local certainty equivalent, global cautious, and local cautious. The filters derived are examined in open loop simulations to determine their identification capabilities independent of the control feedback. Two levels of open loop control variation are used to evaluate estimation performance with constant and time-varying plants. The Kalman filters are found to produce lower estimate errors than the WLS filters. (jhd)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1989
Accession Number
ADA213728

Entities

People

  • Carl R. Knospe
  • J. K. Haviland
  • W. D. Pilkey

Organizations

  • University of Virginia

Tags

Communities of Interest

  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Business Administration
  • Calculus Of Variations
  • Classification
  • Computations
  • Computer Programs
  • Computers
  • Control Systems
  • Engineering
  • Equations
  • Estimators
  • Fast Fourier Transforms
  • Integrals
  • Kalman Filters
  • Materials Science
  • Military Research
  • Sequences

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Control Systems Engineering.