Consensus in multi-agent systems: a review

Abstract

This paper provides a review of the consensus problem as one of the most challenging issues in the distributed control of the multi-agent systems (MASs). In this survey, firstly, the consensus algorithms for the agents with the single-integrator, double-integrator and high-order dynamic models were collected from various research works, and the convergence condition for each of these algorithms was explained. Secondly, all the consensus-related problems such as those in the sampled-data consensus, quantized consensus, random-network consensus, leader-follower consensus, finite-time consensus, bipartite consensus, group consensus/cluster consensus, and the scaled consensus were analyzed and compared with each other. Thirdly, we focused on the common control techniques used for the consensus problems in the presence of disturbance and divided all these control methods into two categories: robust control and adaptive control. Finally, we reviewed the most prevalent consensus applications in the MASs, including the subjects of rendezvous, formation control, axial alignment and the wireless sensor networks.

Engineering Emergence: A Survey on Control in the World of Complex Networks

“…Approaches to consensus are plentiful in the control world [210][211][212][213], although not many deal with complex networks specifically. A recent review [214] on consensus shed light on applications such as rendezvous, formation control, or wireless sensor networks.…”

A Survey of Adaptive Multi-Agent Networks and Their Applications in Smart Cities

“…These dynamics can be expressed as linear or nonlinear models [33]. In linear models, we may be faced with a first-order single integrator that all agents converge to constant values, or double-integrator differential equations, which agents may converge to multiple final states [34]. These models are special forms of general linear models, where the agents are influenced with state and input matrix parameters.…”

Consensus of networked double integrator systems under sensor bias

“…A central condition for exponential convergence of the bias estimation error to zero is Assumption 3. We have, Y Fi (t) = e −βt t 0 e βs Y i ( qi (τ ), qi (τ ), τ ) dτ , where from (7),…”

“…See for example [6] and references therein. A comprehensive survey of the several consensus results in literature can be found in [7]. The preceding references, however, assume perfect measurements or extraneous disturbances only.…”