| dc.contributor |
Junkins , John L . |
|
| dc.creator |
Griffith , Daniel Todd |
|
| dc.date |
2005 -02 -17T21 :00 :34Z |
|
| dc.date |
2005 -02 -17T21 :00 :34Z |
|
| dc.date |
2004 -12 |
|
| dc.date |
2005 -02 -17T21 :00 :34Z |
|
| dc.date.accessioned |
2013 -03 -12T17 :39 :02Z |
|
| dc.date.available |
2013 -03 -12T17 :39 :02Z |
|
| dc.date.issued |
2013 -03 -12 |
|
| dc.identifier |
http : / /hdl .handle .net /1969 .1 /1408 |
|
| dc.identifier.uri |
http : / /hdl .handle .net /1969 .1 /1408 |
|
| dc.description |
The main objective of this work is to demonstrate some new computational methods
for estimation , optimization and modeling of dynamical systems that use automatic
differentiation . Particular focus will be upon dynamical systems arising in Aerospace
Engineering . Automatic differentiation is a recursive computational algorithm , which
enables computation of analytically rigorous partial derivatives of any user -specified
function . All associated computations occur , in the background without user
intervention , as the name implies . The computational methods of this dissertation are
enabled by a new automatic differentiation tool , OCEA (Object oriented Coordinate
Embedding Method ) . OCEA has been recently developed and makes possible efficient
computation and evaluation of partial derivatives with minimal user coding . The key
results in this dissertation details the use of OCEA through a number of computational
studies in estimation and dynamical modeling .
Several prototype problems are studied in order to evaluate judicious ways to use
OCEA . Additionally , new solution methods are introduced in order to ascertain the
extended capability of this new computational tool . Computational tradeoffs are studied
in detail by looking at a number of different applications in the areas of estimation ,
dynamical system modeling , and validation of solution accuracy for complex dynamical
systems . The results of these computational studies provide new insights and indicate
the future potential of OCEA in its further development . |
|
| dc.format |
11948932 bytes |
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| dc.format |
electronic |
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| dc.format |
application /pdf |
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| dc.format |
born digital |
|
| dc.language |
en _US |
|
| dc.publisher |
Texas A &M University |
|
| dc.subject |
automatic differentiation |
|
| dc.subject |
OCEA |
|
| dc.subject |
dynamical systems |
|
| dc.subject |
estimation |
|
| dc.subject |
optimization |
|
| dc.subject |
trajectory optimization |
|
| dc.subject |
orbit determination |
|
| dc.subject |
reversion of series |
|
| dc.subject |
state transition matrix |
|
| dc.subject |
higher -order state transition matrix |
|
| dc.subject |
midcourse correction |
|
| dc.subject |
modeling |
|
| dc.subject |
Lagrange's Equations |
|
| dc.subject |
multibody systems |
|
| dc.subject |
validation |
|
| dc.subject |
method of manfactured solutions |
|
| dc.subject |
method of nearby problems |
|
| dc.subject |
distributed parameter systems |
|
| dc.title |
New methods for estimation , modeling and validation of dynamical systems using automatic differentiation |
|
| dc.type |
Book |
|
| dc.type |
Thesis |
|
| dc.type |
Electronic Dissertation |
|
| dc.type |
text |
|