Min-Max Consensus Algorithm for Multi-agent Systems Subject to Privacy-Preserving Problem

2018 ◽  
pp. 132-142
Author(s):  
Aijuan Wang ◽  
Nankun Mu ◽  
Xiaofeng Liao
Keyword(s):  
Privacy Preserving ◽  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Energy-Balanced Leader-Switching Policy for Formation Rotation Control of Multi-Agent Systems Inspired by Bird Flocks

2019 ◽  
Author(s):  
Corey Dotson ◽  
Geronimo Macias ◽  
Kooktae Lee
Keyword(s):  
Formation Control ◽  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Switching Algorithm ◽  
Multi Agent ◽  
Migrating Birds ◽  
Switching Method ◽  
Rotation Strategy ◽  
Flocking Behavior

Abstract This paper addresses an energy-balanced leader-switching policy for formation rotation control of multi-agent systems inspired by bird flocks. Birds that flock in V-formation with a leader rotation strategy are able to travel longer distances due to reduced drag and therefore less energy expenditure. This flocking behavior with a leader rotation will result in more conservation of overall energy and will be particularly beneficial to migrating birds that should fly long distances without landing. In this paper, we propose an energy-balanced leader-switching policy inspired by this bird flocking behavior in order to increase the flight range for multi-agent systems. The formation control of multi-agent systems is achieved by the consensus algorithm, which is fully decentralized through the use of information exchanges between agents. The proposed leader-switching method is not necessarily incorporated with the consensus dynamics and thus, the leader-switching algorithm can be decoupled from formation control dynamics. Therefore, the proposed method can simplify the leader-switching algorithm, making it easy to implement. Moreover, we propose the analytic flight distance based on the energy consumption model for each agent. To test the validity of the developed method, several simulation results are presented.

Extended consensus algorithm for multi-agent systems

2010 ◽  
Vol 4 (10) ◽  
pp. 2232-2238 ◽  
Author(s):  
G. Zhai ◽  
T. Kobayashi ◽  
S. Okuno ◽  
J. Imae
Keyword(s):  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Fast consensus algorithm of multi-agent systems with double gains regulation

2016 ◽  
Vol 90 (5) ◽  
pp. 1123-1131 ◽  
Author(s):  
Ling-Yun Huang ◽  
Chao Sun ◽  
Sha Fan ◽  
Chun-Xi Yang
Keyword(s):  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics

Automatica ◽  
2011 ◽  
Vol 47 (8) ◽  
pp. 1706-1712 ◽  
Author(s):  
Shihua Li ◽  
Haibo Du ◽  
Xiangze Lin
Keyword(s):  
Finite Time ◽  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Double Integrator

High-accuracy consensus algorithm for second-order multi-agent systems

2018 ◽  
Author(s):  
Feng Jing ◽  
Junfeng Han ◽  
Meilin Xie ◽  
Peng Liu ◽  
Xubin Feng
Keyword(s):  
High Accuracy ◽  
Second Order ◽  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

scholarly journals Algebraic Connectivity Control in Distributed Networks by Using Multiple Communication Channels

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5014
Author(s):  
Karlo Griparić
Keyword(s):  
Communication Channels ◽  
Distributed Networks ◽  
Consensus Algorithm ◽  
Control Law ◽  
Algebraic Connectivity ◽  
Multi Agent Systems ◽  
Robot System ◽  
Agent Systems ◽  
Connectivity Preservation ◽  
Multi Agent

The effectiveness of collaboration in distributed networks, such as sensor networks and multi-agent systems, relies on nodes’ ability to exchange information. The availability of various communication protocols with different technical properties opens the possibility to guarantee connectivity during a system’s operation in any condition. A communication network can be represented by a graph on which connectivity can be expressed by a well-known algebraic connectivity value or Fiedler value. It is one of the most important tools used in many applications where connectivity preservation is required. In this paper, a trust-based consensus algorithm for algebraic connectivity estimation has been implemented. To guarantee the accomplishment of the global objective and the system’s performance, our contributions include: (i) a novel decentralized framework for combining multiple communication channels in a resulting channel and (ii) a decentralized algebraic connectivity control law that dynamically changes the number of agents in the system during operation. The proposed algebraic connectivity control strategy has been evaluated in simulations and in a real multi-robot system using two channels with different properties and initial topologies.

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