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

Linked to FindBook

Google Book

Amazon

博客來

Effective Measurement and Actuation Paradigms for Diffusive Networks.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Effective Measurement and Actuation Paradigms for Diffusive Networks./
Author:	Vosughi, Amirkhosro .
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	201 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-04, Section: B.
Contained By:	Dissertations Abstracts International82-04B.
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27736002
ISBN:	9798678104946

Effective Measurement and Actuation Paradigms for Diffusive Networks.
Vosughi, Amirkhosro .

Effective Measurement and Actuation Paradigms for Diffusive Networks. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 201 p.

Source: Dissertations Abstracts International, Volume: 82-04, Section: B.

Thesis (Ph.D.)--Washington State University, 2020.

This item must not be sold to any third party vendors.

The purpose of this thesis is to investigate the effectiveness of emerging control and monitoring paradigms for dynamical networks, from a graph-theoretic perspective. Two different directions of research are pursued: 1) analysis of target controllability and source estimation metrics for sparsely-actuated and measured network processes, 2) control design for diffusive network processes using stochastically-moving sensors and actuators.First, we study metrics for target controllability and source observability in dynamical networks, which are applicable for assessing security and enabling control in cyber-enabled networks like critical infrastructures. Specifically, the energy required to control a target node in a network from a remote input is characterized, and dually the fidelity with which a source state can be estimated from a remote measurement is studied. Several spectral and graphical results are presented, which allow discernment of the level of difficulty of target control and source estimation, and also permit comparison of the two metrics. Subsequently, scalable distributed algorithms are developed for computing the metrics. The second focus of this study is on analyzing the control of diffusive network processes using stochastically-moving sensors and/or actuators. Breakthroughs in Internet-of-Things technologies are making it possible to have platforms equipped with on-board sensor/actuator that can sense and manipulate network processes locally, even while they are involved in other missions. Here, we consider closed-loop control of diffusive or synchronization processes in networks using such platforms; both continuous-time and sampled-data formulations are considered. The stochastic movement of the platform is modeled by a Markov process, and Markovian Jump Linear System (MJLS) machinery is used to analyze moment stability. Small gain stability in a two-moment sense is verified. The settling time of the closed-loop system is also investigated in the continuous-time context. This framework is subsequently applied to design thermal regularization schemes for residential buildings which use occupant-location data. In this context, the framework is used to statistically characterize a cost metric that incorporates the deviation of temperature from the desired value and control effort. This framework is used to optimize the control parameters.

ISBN: 9798678104946Subjects--Topical Terms:

649834
Electrical engineering.
Subjects--Index Terms:

Cyber security

Effective Measurement and Actuation Paradigms for Diffusive Networks.
LDR:03785nmm a2200433 4500 001 2344560
005 20220531064552.5
008 241004s2020 ||||||||||||||||| ||eng d
020 $a 9798678104946
035 $a (MiAaPQ)AAI27736002
035 $a AAI27736002
040 $a MiAaPQ $c MiAaPQ
100 1 $a Vosughi, Amirkhosro . $0 (orcid)0000-0003-0795-2402 $3 3683347
245 1 0 $a Effective Measurement and Actuation Paradigms for Diffusive Networks.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 201 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-04, Section: B.
500 $a Advisor: Roy, Sandip.
502 $a Thesis (Ph.D.)--Washington State University, 2020.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a The purpose of this thesis is to investigate the effectiveness of emerging control and monitoring paradigms for dynamical networks, from a graph-theoretic perspective. Two different directions of research are pursued: 1) analysis of target controllability and source estimation metrics for sparsely-actuated and measured network processes, 2) control design for diffusive network processes using stochastically-moving sensors and actuators.First, we study metrics for target controllability and source observability in dynamical networks, which are applicable for assessing security and enabling control in cyber-enabled networks like critical infrastructures. Specifically, the energy required to control a target node in a network from a remote input is characterized, and dually the fidelity with which a source state can be estimated from a remote measurement is studied. Several spectral and graphical results are presented, which allow discernment of the level of difficulty of target control and source estimation, and also permit comparison of the two metrics. Subsequently, scalable distributed algorithms are developed for computing the metrics. The second focus of this study is on analyzing the control of diffusive network processes using stochastically-moving sensors and/or actuators. Breakthroughs in Internet-of-Things technologies are making it possible to have platforms equipped with on-board sensor/actuator that can sense and manipulate network processes locally, even while they are involved in other missions. Here, we consider closed-loop control of diffusive or synchronization processes in networks using such platforms; both continuous-time and sampled-data formulations are considered. The stochastic movement of the platform is modeled by a Markov process, and Markovian Jump Linear System (MJLS) machinery is used to analyze moment stability. Small gain stability in a two-moment sense is verified. The settling time of the closed-loop system is also investigated in the continuous-time context. This framework is subsequently applied to design thermal regularization schemes for residential buildings which use occupant-location data. In this context, the framework is used to statistically characterize a cost metric that incorporates the deviation of temperature from the desired value and control effort. This framework is used to optimize the control parameters.
590 $a School code: 0251.
650 4 $a Electrical engineering. $3 649834
650 4 $a Remote sensing. $3 535394
650 4 $a Technical communication. $3 3172863
650 4 $a Systems science. $3 3168411
653 $a Cyber security
653 $a Distributed systems
653 $a Linear systems
653 $a Moving sensor/actuator
653 $a Multi-agent systems
653 $a Stochastic control
653 $a Markovian Jump Linear System
653 $a Thermal regularization
690 $a 0544
690 $a 0643
690 $a 0799
690 $a 0790
710 2 $a Washington State University. $b Electrical Engineering. $3 2098665
773 0 $t Dissertations Abstracts International $g 82-04B.
790 $a 0251
791 $a Ph.D.
792 $a 2020
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27736002