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Distributed Fault Diagnosis for Networked Nonlinear Processes, Multi-Agent Systems, and Source Localization.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Distributed Fault Diagnosis for Networked Nonlinear Processes, Multi-Agent Systems, and Source Localization./
作者:	Noursadeghi, Elaheh.
面頁冊數:	1 online resource (163 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
Contained By:	Dissertation Abstracts International79-01B(E).
標題:	Industrial engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9780355393255

Distributed Fault Diagnosis for Networked Nonlinear Processes, Multi-Agent Systems, and Source Localization.
Noursadeghi, Elaheh.

Distributed Fault Diagnosis for Networked Nonlinear Processes, Multi-Agent Systems, and Source Localization. - 1 online resource (163 pages)

Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.

Thesis (Ph.D.)--University of Massachusetts Lowell, 2017.

Includes bibliographical references

This dissertation deals with the design and development of distributed fault detection and isolation (FDI) methods for large-scale nonlinear uncertain systems. Analytical and computational frameworks are established that allow the distributed monitoring of a monolithic process by a network of diagnostic nodes. Each node is a sensing and inference unit with partial measurement access to the systems variables, and limited computational power. The diagnostic nodes have information-exchange capabilities with their communicating neighbors, which allows them to infer about the health of the system in a distributive manner.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355393255Subjects--Topical Terms:

679492
Industrial engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Distributed Fault Diagnosis for Networked Nonlinear Processes, Multi-Agent Systems, and Source Localization.
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245 1 0 $a Distributed Fault Diagnosis for Networked Nonlinear Processes, Multi-Agent Systems, and Source Localization.
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500 $a Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
500 $a Adviser: Ioannis Raptis.
502 $a Thesis (Ph.D.)--University of Massachusetts Lowell, 2017.
504 $a Includes bibliographical references
520 $a This dissertation deals with the design and development of distributed fault detection and isolation (FDI) methods for large-scale nonlinear uncertain systems. Analytical and computational frameworks are established that allow the distributed monitoring of a monolithic process by a network of diagnostic nodes. Each node is a sensing and inference unit with partial measurement access to the systems variables, and limited computational power. The diagnostic nodes have information-exchange capabilities with their communicating neighbors, which allows them to infer about the health of the system in a distributive manner.
520 $a The first contribution of this dissertation is an FDI approach suitable for processes with geographically remote subsystems. Each diagnostic unit has access to partial measurements of the process variables. The network applies a consensus filter that synchronizes the outputs of the diagnostic nodes. This scheme provides global inference about the health of the system using local observations.
520 $a The second contribution targets nonlinear systems of high order. The monolithic process is subdivided to lower order subsystems. Each subsystem is assigned to a diagnostic unit. The decomposition of the original process can reduce significantly the computational complexity of the local failure-sensitive filters and balance the information sharing between the diagnostic nodes.
520 $a The concept of reduced-order FDI is disseminated to mobile multi-robot systems. The working case study involves robotic fleets that are executing the consensus (or agreement) protocol in the 2-D space while each mobile unit is subjected to velocity biases. The distributed FDI scheme is extended such that each diagnostic node incorporates a local parameter estimator that determines the bearing and magnitude of the velocity bias.
520 $a For the final contribution, the main distributed FDI schemes are modified to tackle the source localization challenge. This part converts the classical FDI scheme for time varying systems to processes that have dependency on both time and space. Two source detection algorithms are proposed that allow for a network of communicating diagnostic nodes to identify collectively the location of the source.
520 $a All the algorithms derived in this work are extensively validated through numerical simulations. Computational issues related to the implementation and complexity of the algorithms, are addressed. Different fault scenarios are considered to demonstrate the detection, isolation and identification capabilities of each algorithm. The simulation results validate the satisfactory performance of the proposed schemes.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
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650 4 $a Robotics. $3 561941
650 4 $a Electrical engineering. $3 596380
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710 2 $a University of Massachusetts Lowell. $3 1179049
773 0 $t Dissertation Abstracts International $g 79-01B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10675310 $z click for full text (PQDT)