Decentralised fault tolerant model predictive control for a class of interconnected system

Ehsan Gatavi; Ali Hellany; Jamal Rizk; Mahmood Nagrial

doi:10.1109/TENCON50793.2020.9293776

Decentralised fault tolerant model predictive control for a class of interconnected system

Ehsan Gatavi, Ali Hellany, Jamal Rizk, Mahmood Nagrial

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

Abstract

![CDATA[A decentralised fault tolerant control is presented in this paper for a class of interconnected system. The bounded control technique is applied to address the interconnection effects and the dynamic changes due to the faults. Multiple local controllers are designed as part of decentralised algorithm to gnarantee the system stability during the fault period. In this case, the system can deal with the fault with large magnitude. To illustrate the effectiveness the proposed scheme, the system is tested for the case that multiple fault occurred in different local subsystems.]]

Original language	English
Title of host publication	Proceedings of 2020 IEEE Region 10 Conference (TENCON), 16-19 November 2020, Osaka, Japan
Publisher	IEEE
Pages	847-851
Number of pages	5
ISBN (Print)	9781728184555
DOIs	https://doi.org/10.1109/TENCON50793.2020.9293776
Publication status	Published - 2020
Event	TENCON - Duration: 16 Nov 2020 → …

Publication series

Name
ISSN (Print)	2159-3450

Conference

Conference	TENCON
Period	16/11/20 → …

Keywords

automatic control
neural networks (computer science)

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10.1109/TENCON50793.2020.9293776

Cite this

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title = "Decentralised fault tolerant model predictive control for a class of interconnected system",

abstract = "![CDATA[A decentralised fault tolerant control is presented in this paper for a class of interconnected system. The bounded control technique is applied to address the interconnection effects and the dynamic changes due to the faults. Multiple local controllers are designed as part of decentralised algorithm to gnarantee the system stability during the fault period. In this case, the system can deal with the fault with large magnitude. To illustrate the effectiveness the proposed scheme, the system is tested for the case that multiple fault occurred in different local subsystems.]]",

keywords = "automatic control, neural networks (computer science)",

author = "Ehsan Gatavi and Ali Hellany and Jamal Rizk and Mahmood Nagrial",

year = "2020",

doi = "10.1109/TENCON50793.2020.9293776",

language = "English",

isbn = "9781728184555",

publisher = "IEEE",

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booktitle = "Proceedings of 2020 IEEE Region 10 Conference (TENCON), 16-19 November 2020, Osaka, Japan",

note = "TENCON ; Conference date: 16-11-2020",

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T1 - Decentralised fault tolerant model predictive control for a class of interconnected system

AU - Gatavi, Ehsan

AU - Hellany, Ali

AU - Rizk, Jamal

AU - Nagrial, Mahmood

PY - 2020

Y1 - 2020

N2 - ![CDATA[A decentralised fault tolerant control is presented in this paper for a class of interconnected system. The bounded control technique is applied to address the interconnection effects and the dynamic changes due to the faults. Multiple local controllers are designed as part of decentralised algorithm to gnarantee the system stability during the fault period. In this case, the system can deal with the fault with large magnitude. To illustrate the effectiveness the proposed scheme, the system is tested for the case that multiple fault occurred in different local subsystems.]]

AB - ![CDATA[A decentralised fault tolerant control is presented in this paper for a class of interconnected system. The bounded control technique is applied to address the interconnection effects and the dynamic changes due to the faults. Multiple local controllers are designed as part of decentralised algorithm to gnarantee the system stability during the fault period. In this case, the system can deal with the fault with large magnitude. To illustrate the effectiveness the proposed scheme, the system is tested for the case that multiple fault occurred in different local subsystems.]]

KW - automatic control

KW - neural networks (computer science)

UR - http://hdl.handle.net/1959.7/uws:58242

U2 - 10.1109/TENCON50793.2020.9293776

DO - 10.1109/TENCON50793.2020.9293776

M3 - Conference Paper

SN - 9781728184555

SP - 847

EP - 851

BT - Proceedings of 2020 IEEE Region 10 Conference (TENCON), 16-19 November 2020, Osaka, Japan

PB - IEEE

T2 - TENCON

Y2 - 16 November 2020

ER -

Decentralised fault tolerant model predictive control for a class of interconnected system

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