Title page for ETD etd-6198-12544


Type of Document Dissertation
Author Doman, David Burke
Author's Email Address doman@apollo.aoe.vt.edu
URN etd-6198-12544
Title Projection Methods for Order Reduction of Optimal Human Operator Models.
Degree PhD
Department Aerospace and Ocean Engineering
Advisory Committee
Advisor Name Title
Anderson, Mark R. Committee Chair
Anderson, Mark R. Committee Member
Cliff, Eugene M. Committee Member
Durham, Wayne C. Committee Member
Lutze, Frederick H. Jr. Committee Member
Robertshaw, Harry H. Committee Member
Keywords
  • Pilot Modeling
  • Man-Machine Systems
  • Human Operstor Modeling
Date of Defense 1998-06-29
Availability unrestricted
Abstract
Human operator models developed using optimal control theory

are typically complicated and over-parameterized, even for

simple controlled elements. Methods for generating less

complicated operator models that preserve the most important

characteristics of the full order model are developed so

that the essential features of the operator dynamics are

easier to determine. A new formulation of the Optimal

Control Model (OCM) of the human operator is developed

that allows order reduction techniques to be applied in

a meaningful way. This formulation preserves the critical

neuromotor dynamics and time delay characteristics of the

human operator. The Optimal Projection (OP) synthesis

technique is applied to a modified version of the OCM.

Using OP synthesis allows one to determine operator models

that minimize the quadratic performance index of the OCM

with a constraint on model order. This technique allows

analysts to formulate operator models of fixed order.

Operator model reduction methods based on variations of

balanced realization techniques are also developed since

they reduce the computational complexity associated with

OP synthesis yet maintain a reasonable level of accuracy.

Computer algorithms are developed that insure that the

reduced order models have noise to signal ratios that are

consistent with OCM theory. The OP method generates

operator models of fixed order that are consistent with

OCM theory in all respects, i.e. optimality, neuromotor

lag, time delay, and noise to signal ratios are all

preserved. The other model reduction techniques preserve

these features with the exception of optimality. Each

technique is applied to a variety of controlled elements

to illustrate how performance and frequency response

fidelity degrade when the order of the operator model is

reduced.

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