Distributed Newton and Quasi-Newton methods for formation control of autonomous vehicles

Mansour Karkoub, Huiwei Wang, Tzu Sung Wu

Research output: Contribution to journalArticle

Abstract

This paper presents a distributed approach based on a Newton-type method for solving the fast formation problems of a group of autonomous underwater vehicles (AUVs) in the plane. Each AUV of this group aims at minimising its own local alignment error function that formulates the difference between the desired relative formation of the AUV and its neighbours and their current positions. In addition, the group jointly minimises the total cost composed by local alignment error functions. The presented approach utilises a modified Jacobi algorithm based on local position data to approximate the Newton direction. It is shown that when combining the descent direction with distributed line search algorithms, the approach exhibits the performance of super-linear convergence within the neighbourhood of the desired position. Two numerical examples are considered here to illustrate that using the proposed approach, all AUVs rapidly achieve the desired formation from any initial configuration and initial position in both static and dynamic formation scenarios.

Original languageEnglish
JournalShips and Offshore Structures
DOIs
Publication statusPublished - 1 Jan 2019

Fingerprint

Autonomous underwater vehicles
Newton-Raphson method
Costs

Keywords

  • Autonomous underwater vehicles
  • distributed newton method
  • formation control
  • leader-follower structure

ASJC Scopus subject areas

  • Ocean Engineering
  • Mechanical Engineering

Cite this

Distributed Newton and Quasi-Newton methods for formation control of autonomous vehicles. / Karkoub, Mansour; Wang, Huiwei; Wu, Tzu Sung.

In: Ships and Offshore Structures, 01.01.2019.

Research output: Contribution to journalArticle

@article{64f50b4601b147adba2520c063bb43ef,
title = "Distributed Newton and Quasi-Newton methods for formation control of autonomous vehicles",
abstract = "This paper presents a distributed approach based on a Newton-type method for solving the fast formation problems of a group of autonomous underwater vehicles (AUVs) in the plane. Each AUV of this group aims at minimising its own local alignment error function that formulates the difference between the desired relative formation of the AUV and its neighbours and their current positions. In addition, the group jointly minimises the total cost composed by local alignment error functions. The presented approach utilises a modified Jacobi algorithm based on local position data to approximate the Newton direction. It is shown that when combining the descent direction with distributed line search algorithms, the approach exhibits the performance of super-linear convergence within the neighbourhood of the desired position. Two numerical examples are considered here to illustrate that using the proposed approach, all AUVs rapidly achieve the desired formation from any initial configuration and initial position in both static and dynamic formation scenarios.",
keywords = "Autonomous underwater vehicles, distributed newton method, formation control, leader-follower structure",
author = "Mansour Karkoub and Huiwei Wang and Wu, {Tzu Sung}",
year = "2019",
month = "1",
day = "1",
doi = "10.1080/17445302.2019.1585620",
language = "English",
journal = "Ships and Offshore Structures",
issn = "1744-5302",
publisher = "Taylor and Francis Ltd.",

}

TY - JOUR

T1 - Distributed Newton and Quasi-Newton methods for formation control of autonomous vehicles

AU - Karkoub, Mansour

AU - Wang, Huiwei

AU - Wu, Tzu Sung

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This paper presents a distributed approach based on a Newton-type method for solving the fast formation problems of a group of autonomous underwater vehicles (AUVs) in the plane. Each AUV of this group aims at minimising its own local alignment error function that formulates the difference between the desired relative formation of the AUV and its neighbours and their current positions. In addition, the group jointly minimises the total cost composed by local alignment error functions. The presented approach utilises a modified Jacobi algorithm based on local position data to approximate the Newton direction. It is shown that when combining the descent direction with distributed line search algorithms, the approach exhibits the performance of super-linear convergence within the neighbourhood of the desired position. Two numerical examples are considered here to illustrate that using the proposed approach, all AUVs rapidly achieve the desired formation from any initial configuration and initial position in both static and dynamic formation scenarios.

AB - This paper presents a distributed approach based on a Newton-type method for solving the fast formation problems of a group of autonomous underwater vehicles (AUVs) in the plane. Each AUV of this group aims at minimising its own local alignment error function that formulates the difference between the desired relative formation of the AUV and its neighbours and their current positions. In addition, the group jointly minimises the total cost composed by local alignment error functions. The presented approach utilises a modified Jacobi algorithm based on local position data to approximate the Newton direction. It is shown that when combining the descent direction with distributed line search algorithms, the approach exhibits the performance of super-linear convergence within the neighbourhood of the desired position. Two numerical examples are considered here to illustrate that using the proposed approach, all AUVs rapidly achieve the desired formation from any initial configuration and initial position in both static and dynamic formation scenarios.

KW - Autonomous underwater vehicles

KW - distributed newton method

KW - formation control

KW - leader-follower structure

UR - http://www.scopus.com/inward/record.url?scp=85062688050&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85062688050&partnerID=8YFLogxK

U2 - 10.1080/17445302.2019.1585620

DO - 10.1080/17445302.2019.1585620

M3 - Article

AN - SCOPUS:85062688050

JO - Ships and Offshore Structures

JF - Ships and Offshore Structures

SN - 1744-5302

ER -