Distributed nonlinear H∞ control algorithm for multi-agent quadrotor formation flying

A novel distributed formation control algorithm for nonlinear uncertain multi-agent systems is proposed in this paper. The algorithm is developed based on a nonlinear H∞ framework for a team of aerial robots with nonlinear dynamics and bounded parametric uncertainties. The multi-agent control algori...

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Bibliographic Details
Published in:ISA transactions Vol. 96; pp. 81 - 94
Main Authors: Rekabi, Fatemeh, Shirazi, Farzad A., Sadigh, Mohammad Jafar
Format: Journal Article
Language:English
Published: United States Elsevier Ltd 01.01.2020
Subjects:
Distributed control
Multi-agent system
Nonlinear [formula omitted]
Quadrotors
Distributed control
Multi-agent system
Nonlinear H
Quadrotors
Nonlinear
ISSN:0019-0578, 1879-2022, 1879-2022
Online Access:Get full text
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Summary:A novel distributed formation control algorithm for nonlinear uncertain multi-agent systems is proposed in this paper. The algorithm is developed based on a nonlinear H∞ framework for a team of aerial robots with nonlinear dynamics and bounded parametric uncertainties. The multi-agent control algorithm reduces to local control laws dependent on agents information and their neighbors data. The proof of stability is presented analytically. Simulation results for two predefined scenarios verify the robust performance of the algorithm in the presence of external disturbances and bounded uncertainties, numerically. Additionally, the effects of communication network configuration are studied using numerical simulations. Calculated ISE and IADU indexes show the effectiveness of the distributed algorithm compared to independent performance of the agents. •A novel distributed formation control law for nonlinear uncertain MAS is proposed.•The algorithm is developed based on NLH∞ theory for a team of aerial robots.•The stability and boundedness of the closed loop system is presented analytically.•Performance evaluation is accomplished using simulation and statistical analysis.•Numerical indexes are used to compare the performance for different network graphs.
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ISSN:0019-0578
1879-2022
1879-2022
DOI:10.1016/j.isatra.2019.04.036