EAN: 9783319248516

ADVANCED TEXTBOOKS IN CONTROL AND SIGNAL PROCES...

For the first time  a textbook that brings together classical predictive control with treatment
of up-to-date robust and stochastic techniques. Model Predictive Control describes the
development of tractable algorithms for uncertain  stochastic  constrained systems. The
starting point is classical predictive control and the appropriate formulation of performance
objectives and constraints to provide guarantees of closed-loop stability and performance.
Moving on to robust predictive control  the text explains how similar guarantees may be
obtained for cases in which the model describing the system dynamics is subject to additive
disturbances and parametric uncertainties. Open- and closed-loop optimization are considered
and the state of the art in computationally tractable methods based on uncertainty tubes
presented for systems with additive model uncertainty. Finally  the tube framework is also
applied to model predictive control problems involving hard or probabilistic constraints for
the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use
of illustrative examples  sample problems  and discussion of novel control applications such as
resource allocation for sustainable development and turbine-blade control for maximized power
capture with simultaneously reduced risk of turbulence-induced damage. Graduate students
pursuing courses in model predictive control or more generally in advanced or process control
and senior undergraduates in need of a specialized treatment will find Model Predictive Control
an invaluable guide to the state of the art in this important subject. For the instructor it
provides an authoritative resource for the construction of courses.

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