Title :
Fast Consensus Via Predictive Pinning Control
Author :
Zhang, Hai-Tao ; Chen, Michael Z Q ; Stan, Guy-Bart
Author_Institution :
State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
By incorporating some predictive mechanism into a few pinning nodes, we show that convergence procedure to consensus can be substantially accelerated in networks of interconnected dynamic agents while physically maintaining the network topology. Such an acceleration stems from the compression mechanism of the eigenspectrum of the state matrix conferred by the predictive mechanism. This study provides a technical basis for the roles of some predictive mechanisms in widely-spread biological swarms, flocks, and consensus networks. From the engineering application point of view, inclusion of an efficient predictive mechanism allows for a significant increase in the convergence speed towards consensus.
Keywords :
convergence; multi-agent systems; predictive control; topology; compression mechanism; convergence procedure; interconnected dynamic agents; multiagent system; network topology; predictive pinning control; state matrix eigenspectrum; widely-spread biological swarms; Acceleration; Biology; Convergence; Eigenvalues and eigenfunctions; Optimization; Protocols; Synchronization; Consensus; multi-agent system (MAS); pinning control; predictive control; synchronization;
Journal_Title :
Circuits and Systems I: Regular Papers, IEEE Transactions on
DOI :
10.1109/TCSI.2011.2123450