Synchronization in Networks of Identical Linear Systems with Reduced Information

Nojavanzadeh

2020 39th Chinese Control Conference (CCC)

et al. 2020

This paper studies global regulated state synchronization of homogeneous networks of non-introspective agents in presence of input saturation. We identify three classes of agent models which are neutrally stable, doubleintegrator, and mixed of double-integrator, single-integrator and neutrally stable dynamics. A scale-free linear observerbased protocol design methodology is developed based on localized information exchange among neighbors where the reference trajectory is given by a so-called exosystem which is assumed to be globally reachable. Our protocols do not need any knowledge about the communication network topology and the spectrum of associated Laplacian matrix. Moreover, the proposed protocol is scalable and is designed based on only knowledge of agent models and achieves synchronization for any communication graph with arbitrary number of agents.

“…Problem 1 Consider a MAS described by (1) and (8) and the associated exosystem (5). Let a set of nodes C be given which defines the set G N C .…”

Section: Definition 1 Given a Node Set C We Denote By G Nmentioning

confidence: 99%

Section: Protocol 1: Full-state Couplingmentioning

confidence: 99%

Section: Protocol 3: Full-state Couplingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Scale-free Linear Observer-based Protocol Design for Global Regulated State Synchronization of Homogeneous Multi-agent Systems with Non-introspective Agents Subject to Input Saturation

Nojavanzadeh

2020 39th Chinese Control Conference (CCC)

et al. 2020

“…Theorem 1 Consider a MAS described by (6) satisfying Assumption 1, with a givenκ and the associated exosystem (2). Let a set of nodes C be given which defines the set G N C and let the asssociated network communication graph G ∈ G N C be given by (10).…”

Section: Full-state Couplingmentioning

confidence: 99%

Global and Semi-global Regulated State Synchronization for Homogeneous Networks of Non-introspective Agents in Presence of Input Saturation- A Scale-free Protocol Design

2019 IEEE 58th Conference on Decision and Control (CDC)

Stoorvogel

et al. 2019

This paper studies regulated state synchronization of discrete-time homogeneous networks of non-introspective agents in presence of unknown non-uniform input delays. A scale free protocol is designed based on additional information exchange, which does not need any knowledge of the directed network topology and the spectrum of the associated Laplacian matrix. The proposed protocol is scalable and achieves state synchronization for any arbitrary number of agents. Meanwhile, an upper bound for the input delay tolerance is obtained, which explicitly depends on the agent dynamics.

Scale‐free collaborative protocols for global regulated state synchronization of discrete‐time homogeneous networks of non‐introspective agents in presence of input saturation

Intl J Robust & Nonlinear

Stoorvogel

2022

This article studies scalable global regulated state synchronization of discrete‐time homogeneous networks of non‐introspective agents in presence of input saturation based on localized information exchange, where the reference trajectory is given by a so‐called exosystem which is assumed to be globally reachable. A scale‐free collaborative nonlinear and linear dynamic protocols design methodology is developed for discrete‐time multi‐agent systems with both full and partial‐state couplings. The scale‐free nonlinear dynamic protocol is developed via design based on scheduling for discrete‐time linear general dynamics. Meanwhile, the scale‐free linear observer‐based protocol design is proposed for a class of neutrally stable discrete‐time agent models. Our protocol design methodology does not need any knowledge of the directed network topology and the spectrum of the associated Laplacian matrix. Moreover, the proposed protocol is scalable and achieves synchronization for any arbitrary number of agents.