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Predictive Approaches to Control of Complex Systems (Hardcover, 2013 ed.)
Loot Price: R3,491
Discovery Miles 34 910
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Predictive Approaches to Control of Complex Systems (Hardcover, 2013 ed.)
Series: Studies in Computational Intelligence, 454
Expected to ship within 12 - 17 working days
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A predictive control algorithm uses a model of the controlled
system to predict the system behavior for various input scenarios
and determines the most appropriate inputs accordingly. Predictive
controllers are suitable for a wide range of systems; therefore,
their advantages are especially evident when dealing with
relatively complex systems, such as nonlinear, constrained, hybrid,
multivariate systems etc. However, designing a predictive control
strategy for a complex system is generally a difficult task,
because all relevant dynamical phenomena have to be considered.
Establishing a suitable model of the system is an essential part of
predictive control design. Classic modeling and identification
approaches based on linear-systems theory are generally
inappropriate for complex systems; hence, models that are able to
appropriately consider complex dynamical properties have to be
employed in a predictive control algorithm. This book first
introduces some modeling frameworks, which can encompass the most
frequently encountered complex dynamical phenomena and are
practically applicable in the proposed predictive control
approaches. Furthermore, unsupervised learning methods that can be
used for complex-system identification are treated. Finally,
several useful predictive control algorithms for complex systems
are proposed and their particular advantages and drawbacks are
discussed. The presented modeling, identification and control
approaches are complemented by illustrative examples. The book is
aimed towards researches and postgraduate students interested in
modeling, identification and control, as well as towards control
engineers needing practically usable advanced control methods for
complex systems.
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