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

Optimal control of energy resources ...

Leong, Alex S.

Linked to FindBook

Google Book

Amazon

博客來

Optimal control of energy resources for state estimation over wireless channels

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimal control of energy resources for state estimation over wireless channels/ by Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey.
Author:	Leong, Alex S.
other author:	Quevedo, Daniel E.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	vii, 125 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction. - Optimal Power Allocation for Kalman Filtering over Fading Channels -- Optimal Transmission Scheduling for Event-Triggered Estimation -- Optimal Transmission Strategies for Remote State Estimation -- Remote State Estimation in Multi-Hop Networks -- Conclusion.
Contained By:	Springer eBooks
Subject:	Electric power systems - State estimation. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-65614-4
ISBN:	9783319656144

Optimal control of energy resources for state estimation over wireless channels
Leong, Alex S.

Optimal control of energy resources for state estimation over wireless channels[electronic resource] /by Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey. - Cham :Springer International Publishing :2018. - vii, 125 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering,2191-8112. - SpringerBriefs in electrical and computer engineering..

Introduction. - Optimal Power Allocation for Kalman Filtering over Fading Channels -- Optimal Transmission Scheduling for Event-Triggered Estimation -- Optimal Transmission Strategies for Remote State Estimation -- Remote State Estimation in Multi-Hop Networks -- Conclusion.

This brief introduces wireless communications ideas and techniques into the study of networked control systems. It focuses on state estimation problems in which sensor measurements (or related quantities) are transmitted over wireless links to a central observer. Wireless communications techniques are used for energy resource management in order to improve the performance of the estimator when transmission occurs over packet dropping links, taking energy use into account explicitly in Kalman filtering and control. The brief allows a reduction in the conservatism of control designs by taking advantage of the assumed. The brief shows how energy-harvesting-based rechargeable batteries or storage devices can offer significant advantages in the deployment of large-scale wireless sensor and actuator networks by avoiding the cost-prohibitive task of battery replacement and allowing self-sustaining sensor to be operation. In contrast with research on energy harvesting largely focused on resource allocation for wireless communication systems design, this brief optimizes estimation objectives such as minimizing the expected estimation error covariance. The resulting power control problems are often stochastic control problems which take into account both system and channel dynamics. The authors show how to pose and solve such design problems using dynamic programming techniques. Researchers and graduate students studying networked control systems will find this brief a helpful source of new ideas and research approaches.

ISBN: 9783319656144

Standard No.: 10.1007/978-3-319-65614-4doiSubjects--Topical Terms:

3295989
Electric power systems
--State estimation.

LC Class. No.: TK1005

Dewey Class. No.: 621.31

Optimal control of energy resources for state estimation over wireless channels
LDR:02872nmm a2200325 a 4500 001 2130935
003 DE-He213
005 20170816104609.0
006 m d
007 cr nn 008maaau
008 181005s2018 gw s 0 eng d
020 $a 9783319656144 $q (electronic bk.)
020 $a 9783319656137 $q (paper)
024 7 $a 10.1007/978-3-319-65614-4 $2 doi
035 $a 978-3-319-65614-4
040 $a GP $c GP
041 0 $a eng
050 4 $a TK1005
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
082 0 4 $a 621.31 $2 23
090 $a TK1005 $b .L583 2018
100 1 $a Leong, Alex S. $3 3295986
245 1 0 $a Optimal control of energy resources for state estimation over wireless channels $h [electronic resource] / $c by Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a vii, 125 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in electrical and computer engineering, $x 2191-8112
505 0 $a Introduction. - Optimal Power Allocation for Kalman Filtering over Fading Channels -- Optimal Transmission Scheduling for Event-Triggered Estimation -- Optimal Transmission Strategies for Remote State Estimation -- Remote State Estimation in Multi-Hop Networks -- Conclusion.
520 $a This brief introduces wireless communications ideas and techniques into the study of networked control systems. It focuses on state estimation problems in which sensor measurements (or related quantities) are transmitted over wireless links to a central observer. Wireless communications techniques are used for energy resource management in order to improve the performance of the estimator when transmission occurs over packet dropping links, taking energy use into account explicitly in Kalman filtering and control. The brief allows a reduction in the conservatism of control designs by taking advantage of the assumed. The brief shows how energy-harvesting-based rechargeable batteries or storage devices can offer significant advantages in the deployment of large-scale wireless sensor and actuator networks by avoiding the cost-prohibitive task of battery replacement and allowing self-sustaining sensor to be operation. In contrast with research on energy harvesting largely focused on resource allocation for wireless communication systems design, this brief optimizes estimation objectives such as minimizing the expected estimation error covariance. The resulting power control problems are often stochastic control problems which take into account both system and channel dynamics. The authors show how to pose and solve such design problems using dynamic programming techniques. Researchers and graduate students studying networked control systems will find this brief a helpful source of new ideas and research approaches.
650 0 $a Electric power systems $x State estimation. $3 3295989
650 0 $a Control theory. $3 535880
650 1 4 $a Engineering. $3 586835
650 2 4 $a Control. $3 1006321
650 2 4 $a Information Systems Applications (incl. Internet) $3 1565452
650 2 4 $a Communications Engineering, Networks. $3 891094
700 1 $a Quevedo, Daniel E. $3 3295987
700 1 $a Dey, Subhrakanti. $3 3295988
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in electrical and computer engineering. $3 1565565
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-65614-4
950 $a Engineering (Springer-11647)