東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Model predictive control = classical...

Kouvaritakis, Basil.

Linked to FindBook

Google Book

Amazon

博客來

Model predictive control = classical, robust and stochastic /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model predictive control/ by Basil Kouvaritakis, Mark Cannon.
Reminder of title:	classical, robust and stochastic /
Author:	Kouvaritakis, Basil.
other author:	Cannon, Mark.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xiii, 384 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	From the Contents: Introduction -- Classical Model Predictive Control -- Robust Model Predictive Control with Additive Uncertainty: Open-loop Optimization Strategies -- Robust Model Predictive Control with Additive Uncertainty: Closed-loop Optimization Strategies.
Contained By:	Springer eBooks
Subject:	Predictive control. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-24853-0
ISBN:	9783319248530$q(electronic bk.)

Model predictive control = classical, robust and stochastic /
Kouvaritakis, Basil.

Model predictive controlclassical, robust and stochastic /[electronic resource] :by Basil Kouvaritakis, Mark Cannon. - Cham :Springer International Publishing :2016. - xiii, 384 p. :ill. (some col.), digital ;24 cm. - Advanced textbooks in control and signal processing,1439-2232. - Advanced textbooks in control and signal processing..

From the Contents: Introduction -- Classical Model Predictive Control -- Robust Model Predictive Control with Additive Uncertainty: Open-loop Optimization Strategies -- Robust Model Predictive Control with Additive Uncertainty: Closed-loop Optimization Strategies.

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.

ISBN: 9783319248530$q(electronic bk.)

Standard No.: 10.1007/978-3-319-24853-0doiSubjects--Topical Terms:

667592
Predictive control.

LC Class. No.: TJ217.6

Dewey Class. No.: 629.8

Model predictive control = classical, robust and stochastic /
LDR:03025nmm a2200325 a 4500 001 2029883
003 DE-He213
005 20160808120518.0
006 m d
007 cr nn 008maaau
008 160908s2016 gw s 0 eng d
020 $a 9783319248530$q(electronic bk.)
020 $a 9783319248516$q(paper)
024 7 $a 10.1007/978-3-319-24853-0 $2 doi
035 $a 978-3-319-24853-0
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ217.6
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
082 0 4 $a 629.8 $2 23
090 $a TJ217.6 $b .K88 2016
100 1 $a Kouvaritakis, Basil. $3 2181193
245 1 0 $a Model predictive control $h [electronic resource] : $b classical, robust and stochastic / $c by Basil Kouvaritakis, Mark Cannon.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xiii, 384 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Advanced textbooks in control and signal processing, $x 1439-2232
505 0 $a From the Contents: Introduction -- Classical Model Predictive Control -- Robust Model Predictive Control with Additive Uncertainty: Open-loop Optimization Strategies -- Robust Model Predictive Control with Additive Uncertainty: Closed-loop Optimization Strategies.
520 $a 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.
650 0 $a Predictive control. $3 667592
650 0 $a Engineering. $3 586835
650 0 $a Chemical engineering. $3 560457
650 0 $a System theory. $3 525574
650 0 $a Automotive engineering. $3 2181195
650 0 $a Aerospace engineering. $3 1002622
650 0 $a Astronautics. $3 524166
650 0 $a Automatic control. $3 535879
650 2 4 $a Control. $3 1006321
650 2 4 $a Systems Theory, Control. $3 893834
650 2 4 $a Industrial Chemistry/Chemical Engineering. $3 890826
650 2 4 $a Automotive Engineering. $3 928032
650 2 4 $a Aerospace Technology and Astronautics. $3 928116
700 1 $a Cannon, Mark. $3 2181194
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Advanced textbooks in control and signal processing. $3 1027197
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-24853-0
950 $a Engineering (Springer-11647)