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This book is the result of over ten (10) years of research and
development in flexible robots and structures at Sandia National
Laboratories. The authors de cided to collect this wealth of
knowledge into a set of viewgraphs in order to teach a graduate
class in Flexible Robot Dynamics and Controls within the Mechanical
En gineering Department at the University of New Mexico (UNM).
These viewgraphs, encouragement from several students, and many
late nights have produced a book that should provide an upper-level
undergraduate and graduate textbook and a reference for experienced
professionals. The content of this book spans several disciplines
including structural dynam ics, system identification,
optimization, and linear, digital, and nonlinear control theory
which are developed from several points of view including
electrical, me chanical, and aerospace engineering as well as
engineering mechanics. As a result, the authors believe that this
book demonstrates the value of solid applied theory when developing
hardware solutions to real world problems. The reader will find
many real world applications in this book and will be shown the
applicability of these techniques beyond flexible structures which,
in turn, shows the value of mul tidisciplinary education and
teaming.
This book is the result of over ten (10) years of research and
development in flexible robots and structures at Sandia National
Laboratories. The authors de cided to collect this wealth of
knowledge into a set of viewgraphs in order to teach a graduate
class in Flexible Robot Dynamics and Controls within the Mechanical
En gineering Department at the University of New Mexico (UNM).
These viewgraphs, encouragement from several students, and many
late nights have produced a book that should provide an upper-level
undergraduate and graduate textbook and a reference for experienced
professionals. The content of this book spans several disciplines
including structural dynam ics, system identification,
optimization, and linear, digital, and nonlinear control theory
which are developed from several points of view including
electrical, me chanical, and aerospace engineering as well as
engineering mechanics. As a result, the authors believe that this
book demonstrates the value of solid applied theory when developing
hardware solutions to real world problems. The reader will find
many real world applications in this book and will be shown the
applicability of these techniques beyond flexible structures which,
in turn, shows the value of mul tidisciplinary education and
teaming."
Based on the results of over 10 years of research and development
by the authors, this book presents a broad cross section of dynamic
programming (DP) techniques applied to the optimization of
dynamical systems. The main goal of the research effort was to
develop a robust path planning/trajectory optimization tool that
did not require an initial guess. The goal was partially met with a
combination of DP and homotopy algorithms. DP algorithms are
presented here with a theoretical development, and their successful
application to variety of practical engineering problems is
emphasized. Applied Dynamic Programming for Optimization of
Dynamical Systems presents applications of DP algorithms that are
easily adapted to the reader's own interests and problems. The book
is organized in such a way that it is possible for readers to use
DP algorithms before thoroughly comprehending the full theoretical
development. A general architecture is introduced for DP algorithms
emphasizing the solution to nonlinear problems. DP algorithm
development is introduced gradually with illustrative examples that
surround linear systems applications. Many examples and explicit
design steps applied to case studies illustrate the ideas and
principles behind DP algorithms. DP algorithms potentially address
a wide class of applications composed of many different physical
systems described by dynamical equations of motion that require
optimized trajectories for effective maneuverability. The DP
algorithms determine control inputs and corresponding state
histories of dynamic systems for a specified time while minimizing
a performance index. Constraints may be applied to the final states
of the dynamic system or to the states and control inputs during
the transient portion of the manoeuvre.
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