國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Model predictive controlclassical, r...

Cannon, Mark.

Model predictive controlclassical, robust and stochastic /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Model predictive controlby Basil Kouvaritakis, Mark Cannon.
其他題名:	classical, robust and stochastic /
作者:	Kouvaritakis, Basil.
其他作者:	Cannon, Mark.
出版者:	Cham :Springer International Publishing :2016.
面頁冊數:	xiii, 384 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Predictive control.
電子資源:	http://dx.doi.org/10.1007/978-3-319-24853-0
ISBN:	9783319248530$q(electronic bk.)

Model predictive controlclassical, 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:

182316
Predictive control.

LC Class. No.: TJ217.6

Dewey Class. No.: 629.8

Model predictive controlclassical, robust and stochastic /
LDR:03025nmm a2200325 a 4500 001 482359
003 DE-He213
005 20160808120518.0
006 m d
007 cr nn 008maaau
008 161007s2016 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 739046
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 182316
650 0 $a Engineering. $3 210888
650 0 $a Chemical engineering. $3 206267
650 0 $a System theory. $3 183989
650 0 $a Automotive engineering. $3 739048
650 0 $a Aerospace engineering. $3 324294
650 0 $a Astronautics. $3 274036
650 0 $a Automatic control. $3 182078
650 2 4 $a Control. $3 349080
650 2 4 $a Systems Theory, Control. $3 274654
650 2 4 $a Industrial Chemistry/Chemical Engineering. $3 273974
650 2 4 $a Automotive Engineering. $3 308930
650 2 4 $a Aerospace Technology and Astronautics. $3 309707
700 1 $a Cannon, Mark. $3 739047
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Advanced textbooks in control and signal processing. $3 677001
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-24853-0
950 $a Engineering (Springer-11647)