Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 400 pp. Englisch. Seller Inventory # 9783319796895

Contact seller

Buy New

US$ 94.16

Convert currency

Shipping: US$ 26.20

From Germany to U.S.A.

Destination, rates & speeds

Quantity: 2 available

Add to basket

Seller Image

Model Predictive Control : Classical, Robust and Stochastic

Kouvaritakis, Basil; Cannon, Mark

Published by Springer, 2019

ISBN 10: 3319796895 ISBN 13: 9783319796895

New Softcover

Seller: GreatBookPrices, Columbia, MD, U.S.A.

Seller rating 5 out of 5 stars

Condition: New. Seller Inventory # 34975149-n

Contact seller

Buy New

US$ 117.75

Convert currency

Shipping: US$ 2.64

Within U.S.A.

Destination, rates & speeds

Quantity: Over 20 available

Add to basket

Seller Image

Model Predictive Control : Classical, Robust and Stochastic

Mark Cannon

Published by Springer International Publishing, Springer Nature Switzerland, 2019

ISBN 10: 3319796895 ISBN 13: 9783319796895

New Taschenbuch

Seller: AHA-BUCH GmbH, Einbeck, Germany

Seller rating 5 out of 5 stars

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783319796895

Contact seller