Distributed average consensus based on structural weight‐balanceability. Issue 2 (1st January 2015)

• Record Type: Journal Article
• Authors: Haghighi, Reza; Cheah, Chien Chern
• Is Part Of: IET control theory & applications. Volume 9:Issue 2(2015)
• Page Start: 176
• Page End: 183
• Publication Date: 2015-01-01
• Subjects: networked control systems -- directed graphs -- matrix algebra -- observability -- distributed decision making -- network theory (graphs); structural weight balanceability -- network control systems -- distributed average consensus -- structural observability -- structurally unobservable node identification -- mathematical method -- Laplacian matrix -- structurally weight balanceable network -- distributed method -- directed communication topology; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2014.0251
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : This study presents the concept of structural weight‐balanceability of network systems as a useful method to examine the average consensus of the systems. The authors introduce the notion of structurally unobservable node based on structural observability concept to determine the structural weight‐balanceability of a network. They propose a simple technique to identify structurally unobservable nodes, and consequently infer on structural weight‐balanceability of the network. A mathematical method based on principal minors of the associated Laplacian matrix of the network is developed to modify a structurally weight‐balanceable network into a weight‐balanced one. A distributed method is presented to compute normalised principal minors in a large‐scale network system with directed communication topology. This is the first work that provides a rigorous mathematical formulation to check the structural weight‐balanceability of network systems and make a structurally weight‐balanceable network, weight‐balanced. Finally, simulation results are presented to illustrate the performance of the proposed method in dealing with networks with a large number of nodes.