Distributed Robustness Analysis of Heterogeneous Networks Via Integral Quadratic Constraints
Khong, Sei Zhen LU and Rantzer, Anders LU
(2015)
American Control Conference, 2015
- Abstract
- Robust performance of networks of interconnected heterogenous nonlinear dynamic systems is studied using the theory of integral quadratic constraints. By appealing to recent results on chordal sparsity decompositions of rational transfer matrices, distributed and scalable certificates for performance of interconnections are proposed. The approach is more direct since it does not involve reformulating the problem in terms of standard closed-loop configurations as is typical in the literature, which may destroy or conceal the structural properties inherent in the interconnections. The well-studied notion of feedback performance is reinvestigated within this framework. It is shown that feedback performance can be verified in a distributed... (More)
- Robust performance of networks of interconnected heterogenous nonlinear dynamic systems is studied using the theory of integral quadratic constraints. By appealing to recent results on chordal sparsity decompositions of rational transfer matrices, distributed and scalable certificates for performance of interconnections are proposed. The approach is more direct since it does not involve reformulating the problem in terms of standard closed-loop configurations as is typical in the literature, which may destroy or conceal the structural properties inherent in the interconnections. The well-studied notion of feedback performance is reinvestigated within this framework. It is shown that feedback performance can be verified in a distributed fashion if the signal variables in the feedback interconnection are selected appropriately. Another contribution of the paper lies in identifying three chordality-preserving operations that are standard in control and modelling theory, namely local feedback, feedforward, and additive input-output perturbations. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7763970
- author
- Khong, Sei Zhen
LU
and Rantzer, Anders
LU
- organization
- publishing date
- 2015
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- American Control Conference, 2015
- conference name
- American Control Conference, 2015
- conference location
- Chicago, IL, United States
- conference dates
- 2015-07-01 - 2015-07-03
- external identifiers
-
- scopus:84940928176
- language
- English
- LU publication?
- yes
- id
- d051c199-7592-4298-a9ee-cf7cc869ea74 (old id 7763970)
- date added to LUP
- 2016-04-04 14:27:05
- date last changed
- 2023-09-06 22:26:28
@inproceedings{d051c199-7592-4298-a9ee-cf7cc869ea74,
abstract = {{Robust performance of networks of interconnected heterogenous nonlinear dynamic systems is studied using the theory of integral quadratic constraints. By appealing to recent results on chordal sparsity decompositions of rational transfer matrices, distributed and scalable certificates for performance of interconnections are proposed. The approach is more direct since it does not involve reformulating the problem in terms of standard closed-loop configurations as is typical in the literature, which may destroy or conceal the structural properties inherent in the interconnections. The well-studied notion of feedback performance is reinvestigated within this framework. It is shown that feedback performance can be verified in a distributed fashion if the signal variables in the feedback interconnection are selected appropriately. Another contribution of the paper lies in identifying three chordality-preserving operations that are standard in control and modelling theory, namely local feedback, feedforward, and additive input-output perturbations.}},
author = {{Khong, Sei Zhen and Rantzer, Anders}},
booktitle = {{American Control Conference, 2015}},
language = {{eng}},
title = {{Distributed Robustness Analysis of Heterogeneous Networks Via Integral Quadratic Constraints}},
year = {{2015}},
}