

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 Doctor of Philosophy Department Aerospace and Ocean Engineering Advisory Committee
Advisor Name Title Mark R. Anderson Committee Chair Eugene M. Cliff Committee Member Frederick H. Lutze Committee Member Harry H. Robertshaw Committee Member Mark R. Anderson Committee Member Wayne C. Durham 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 theoryare 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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