Robustness Properties of Distributed Configurations in Multi-Agent Systems. This work was supported by a City University scholarship held by Ivana Tomi.

作     者：Tomi, Ivana Halikias, George D. 

作者机构：Research Centre for Systems & Control School of Mathematics Computer Science and Engineering City University Northampton Square LondonEC1V 0HB United Kingdom 

出 版 物：《IFAC-PapersOnLine》 

年 卷 期：2016年第49卷第9期

页      面：86-91页

核心收录：

基　　金：★★ This work was supported by a City Unifiersity scholarship held by ★ This work was supported by a City Unifiersity scholarship held by IfiaTnhaisTwomorikć.was supported by a City Unifiersity scholarship held by Ifiana Tomić. Ifiana Tomić 

主　　题：Multi agent systems Distributed computer systems Distributed parameter control systems Robustness (control systems) Vector spaces Centralized controllers Distributed configuration Distributed control Distributed control schemes Linear quadratic regulator Multiagent networks Performance costs Robustness properties 

摘      要：This paper considers a distributed LQR design framework for a multi-agent network consisting of identical dynamically decoupled agents. A systematic method is presented for computing the performance loss of various distributed control configurations relative to the performance of the optimal centralized controller. Necessary and sufficient conditions have been derived for which a distributed control configuration pattern arising from the optimal centralizing solution does not entail loss of performance if the initial vector lies in a certain subspace of state-space which is identified. It was shown that these conditions are always satisfied for systems with communication/control networks corresponding to complete graphs with a single link removed. A procedure is extended for analyzing the performance loss of an arbitrary distributed configuration which is illustrated by an exhaustive analysis of a network consisting of agents described by second-order integrator dynamics. Presented results are useful for quantifying performance loss due to decentralization and for designing optimal or near-optimal distributed control schemes. © 2015