Synchronization in networks of identical linear systems
By Luca Scardovi, Rodolphe Sepulchre. 2008
867 citations recorded by the source corpus.
The paper investigates the synchronization of a network of identical linear time-invariant state-space models under a possibly time-varying and directed interconnection structure. The main result is the construction of a dynamic output feedback coupling that achieves synchronization if the decoupled systems have no exponentially unstable mode and if the communication graph is uniformly connected. Stronger conditions are shown to be sufficient - but to some extent, also necessary - to ensure synchronization with the diffusive static output coupling often considered in the literature.
Subfields: Computer Networks and Communications
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In Computer Networks and Communications
Citations in the corpus
- Optimal Design for Synchronization of Cooperative Systems: State Feedback, Observer and Output Feedback (2011, background): “Remark 1: In literature of leaderless consensus, e.g., , , it is often required that all eigenvalues of sit in the closed left-half complex plane [ 15 ], [16].”
- Optimal Synchronization for Networks of Noisy Double Integrators (2011, background): “Most of the available results are for synchronization of either nonidentical systems which are strictly stable [5], or identical linear systems [ 9 ], [13].”
- Decentralized event-triggered consensus with general linear dynamics (2014, methodology): “The single integrator ismodeled as a ZOHand the double integrator is modeled similar to Seyboth et al. (2013), that is, velocity as a ZOH and position as a first-order-hold model.”
- Consensus of Multiagent Systems and Synchronization of Complex Networks: A Unified Viewpoint (2016, methodology): “Second, an observer-type consensus protocol is proposed, which is based on relative output measurements between neighboring agents, in contrast to [39] where a full-state coupling law is used and to [37] where the dynamic protocol requires the absolute output of each agent to be available.”
- Global consensus for discrete-time multi-agent systems with input saturation constraints (2014, background): “where the agent models are identical) has been considered (e.g., Olfati-Saber and Murray, 2004; Ren and Beard, 2005; Xiao and Wang, 2008; Scardovi and Sepulchre, 2009; Seo, Shim, and Back, 2009; Shi and Hong, 2009; Li, Duan, Chen, and Huang, 2010; Li, Du, and Lin, 2011a; Yu, Chen, and Cao, 2010; Yan”
- Recent Advances in Consensus of Multi-Agent Systems: A Brief Survey (2017, background): “[84], consensus with delays [10], [59], [61], [78], [91], [100], [104], optimal consensus [32], [50], [79], sampled-data consensus [61], adaptive consensus [17], [119], quantized consensus”
- Consensus of Multi-Agent Systems With General Linear and Lipschitz Nonlinear Dynamics Using Distributed Adaptive Protocols (2011, background): “However, contrary to this technical brief, output feedback controllers have been employed in [14], [16], [17].”
- Distributed control gains design for consensus in multi-agent systems with second-order nonlinear dynamics (2013, background): “…been recently achieved in investigating synchronization in networks of identical linear systems, where synchronization can be reached if the linear system satisfies some assumptions and the network is connected (Dzhunusov & Fradkov, 2011; Li, Duan, Chen, & Huang, 2010; Scardovi & Sepulchre, 2009).”
- Containment of Higher-Order Multi-Leader Multi-Agent Systems: A Dynamic Output Approach (2016, background): “Note that this is also a common assumption in the existing works on distributed output feedback control of linear multi-agent systems [13], [27], [29].”
- Stability of a Class of Linear Switching Systems with Applications to Two Consensus Problems (2011, background): “On the other hand, one can find examples that satisfy Assumptions 2 and 3, but not condition (ii) of [21].”
- Synchronization of Networks of Nonidentical Euler-Lagrange Systems With Uncertain Parameters and Communication Delays (2011, background): “• In the spirit of [5], [30], it would be desirable to implement an observer-based controller that does not require the measurement of velocities.”