On the sensitivity of the control structure selection problems in large scale multivariable systems

Amin Nobakhti; Martin Brown; Hong Wang

doi:10.1109/CDC.2007.4434220

On the sensitivity of the control structure selection problems in large scale multivariable systems

Amin Nobakhti, Martin Brown, Hong Wang

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

Abstract

Current approaches to solve the control structure selection problem either rely on the control engineer's experience and intuition, or solutions of difficult and nonconvex combinatorial optimisation problems. In this paper a set of new computationally inexpensive graphical analysis tools based on basis pursuit regularization methods are presented which provide significant insight into the control structure selection problem. With the aid of an example it is shown how these tools are used directly to assess the local structural sensitivity of the problem and identify key and important connections within the controller. © 2007 IEEE.

Original language	English
Title of host publication	Proceedings of the IEEE Conference on Decision and Control\|Proc IEEE Conf Decis Control
Pages	4116-4121
Number of pages	5
DOIs	https://doi.org/10.1109/CDC.2007.4434220
Publication status	Published - 2007
Event	46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA Duration: 1 Jul 2007 → …

Conference

Conference	46th IEEE Conference on Decision and Control 2007, CDC
City	New Orleans, LA
Period	1/07/07 → …

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10.1109/CDC.2007.4434220

Cite this

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title = "On the sensitivity of the control structure selection problems in large scale multivariable systems",

abstract = "Current approaches to solve the control structure selection problem either rely on the control engineer's experience and intuition, or solutions of difficult and nonconvex combinatorial optimisation problems. In this paper a set of new computationally inexpensive graphical analysis tools based on basis pursuit regularization methods are presented which provide significant insight into the control structure selection problem. With the aid of an example it is shown how these tools are used directly to assess the local structural sensitivity of the problem and identify key and important connections within the controller. {\textcopyright} 2007 IEEE.",

author = "Amin Nobakhti and Martin Brown and Hong Wang",

year = "2007",

doi = "10.1109/CDC.2007.4434220",

language = "English",

isbn = "1424414989",

pages = "4116--4121",

booktitle = "Proceedings of the IEEE Conference on Decision and Control|Proc IEEE Conf Decis Control",

note = "46th IEEE Conference on Decision and Control 2007, CDC ; Conference date: 01-07-2007",

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AU - Brown, Martin

AU - Wang, Hong

PY - 2007

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AB - Current approaches to solve the control structure selection problem either rely on the control engineer's experience and intuition, or solutions of difficult and nonconvex combinatorial optimisation problems. In this paper a set of new computationally inexpensive graphical analysis tools based on basis pursuit regularization methods are presented which provide significant insight into the control structure selection problem. With the aid of an example it is shown how these tools are used directly to assess the local structural sensitivity of the problem and identify key and important connections within the controller. © 2007 IEEE.

U2 - 10.1109/CDC.2007.4434220

DO - 10.1109/CDC.2007.4434220

M3 - Conference contribution

SN - 1424414989

SN - 9781424414987

SP - 4116

EP - 4121

BT - Proceedings of the IEEE Conference on Decision and Control|Proc IEEE Conf Decis Control

T2 - 46th IEEE Conference on Decision and Control 2007, CDC

Y2 - 1 July 2007

ER -

On the sensitivity of the control structure selection problems in large scale multivariable systems

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