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A New Weighted Graph-Based Partitioning Algorithm for Decentralized Nonlinear Model Predictive Control of Large-Scale Systems

by Karim Salahshoor, Saeed Kamelian
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 40 - Number 14
Year of Publication: 2012
Authors: Karim Salahshoor, Saeed Kamelian
10.5120/5046-6915

Karim Salahshoor, Saeed Kamelian . A New Weighted Graph-Based Partitioning Algorithm for Decentralized Nonlinear Model Predictive Control of Large-Scale Systems. International Journal of Computer Applications. 40, 14 ( February 2012), 7-14. DOI=10.5120/5046-6915

@article{ 10.5120/5046-6915,
author = { Karim Salahshoor, Saeed Kamelian },
title = { A New Weighted Graph-Based Partitioning Algorithm for Decentralized Nonlinear Model Predictive Control of Large-Scale Systems },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 40 },
number = { 14 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 7-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume40/number14/5046-6915/ },
doi = { 10.5120/5046-6915 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:28:02.905729+05:30
%A Karim Salahshoor
%A Saeed Kamelian
%T A New Weighted Graph-Based Partitioning Algorithm for Decentralized Nonlinear Model Predictive Control of Large-Scale Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 40
%N 14
%P 7-14
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper proposes a grouping algorithm for partitioning large-scale nonlinear dynamical systems based on graph theory. The algorithm incorporates a novel scheme to quantify the strengths of graph edges, representing the degree of couplings among the system variables via sensitivity functions. This leads to a weighted graph topology with different weights on the obtained graph edges. An algorithm is then developed to partition systems into some sub-graphs based on the weighted graph. A decentralized nonlinear model predictive control (NMPC) methodology is then formulated for the sub-systems. The overall NMPC design methodology is finally evaluated on a process plant benchmark, consisting of two continuous stirred tank reactors (CSTRs) and a flash separator with a recycle path. A set of tracking and regulatory tests is comparatively conducted exploring the successful performance of the proposed algorithm in the context of the decentralized NMPC methodology with respect to an alternative centralized NMPC control scheme.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Graph partitioning algorithm Decentralized control nonlinear model predictive controller Large-scale systems.

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