Optimal sparse output feedback for networked systems with parametric uncertainties

Ahmadreza Argha; Steven W. Su; Lin Ye; Branko G. Celler

doi:10.3934/naco.2019019

Article Contents

2019, Volume 9, Issue 3: 283-295. Doi: 10.3934/naco.2019019

This issue Previous Article A resilient convex combination for consensus-based distributed algorithms Next Article Identification of Hessian matrix in distributed gradient-based multi-agent coordination control systems

Optimal sparse output feedback for networked systems with parametric uncertainties

1.
School of Electrical Engineering and Telecommunications, University of New South Wales, NSW 2052 Australia
2.
Faculty of Engineering and Information Technology, University of Technology, Sydney (UTS), PO Box 123, Broadway, NSW 2007, Australia

^* Corresponding author: steven.su@uts.edu.au
^* Corresponding author: steven.su@uts.edu.au

Received: May 2018

Revised: April 2019

Published: May 2019

An earlier version of the paper appears in the proceedings of American Control Conference 2018.

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Abstract

This paper investigates the design of block row/column-sparse distributed static output ${H}_2$ feedback control for interconnected systems with polytopic uncertainties. The proposed approach is applicable to the networked systems with publisher/subscriber communication topology. We added two additional terms into the optimisation index function to penalise the number of publishers and subscribers. To optimally select a subset of available publishers and/or subscribers in the network, we introduced both an explicit scheme and an iterative process to handle this problem. We demonstrated the effectiveness by using a numerical example. The example showed that the simultaneous identification of favourable networks topologies and design of controller strategy can be achieved by using the proposed method.

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Mathematics Subject Classification: Primary: 90C22, 90C35; Secondary: 93A15.

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Figure 1. Networked System Architecture

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Figure 2. Structure of block row/column-sparse SOF gains for different values of $\Psi_s$ and $\Psi_p$

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