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Iterative Learning Control - An Optimization Paradigm (Hardcover, 1st ed. 2016)
Loot Price: R5,823
Discovery Miles 58 230
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Iterative Learning Control - An Optimization Paradigm (Hardcover, 1st ed. 2016)
Series: Advances in Industrial Control
Expected to ship within 10 - 15 working days
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This book develops a coherent and quite general theoretical
approach to algorithm design for iterative learning control based
on the use of operator representations and quadratic optimization
concepts including the related ideas of inverse model control and
gradient-based design. Using detailed examples taken from linear,
discrete and continuous-time systems, the author gives the reader
access to theories based on either signal or parameter
optimization. Although the two approaches are shown to be related
in a formal mathematical sense, the text presents them separately
as their relevant algorithm design issues are distinct and give
rise to different performance capabilities. Together with algorithm
design, the text demonstrates the underlying robustness of the
paradigm and also includes new control laws that are capable of
incorporating input and output constraints, enable the algorithm to
reconfigure systematically in order to meet the requirements of
different reference and auxiliary signals and also to support new
properties such as spectral annihilation. Iterative Learning
Control will interest academics and graduate students working in
control who will find it a useful reference to the current status
of a powerful and increasingly popular method of control. The depth
of background theory and links to practical systems will be of use
to engineers responsible for precision repetitive processes.
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