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lyapunov-based-formation-control-of-underwater-robots

Addressing novel Lyapunov-based tracking formation control with nonlinear dynamics, stability analysis and practical efficiency demonstrated in diverse scenarios.

https://github.com/rasoul-zahedifar/lyapunov-based-formation-control-of-underwater-robots

Science Score: 57.0%

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Repository

Addressing novel Lyapunov-based tracking formation control with nonlinear dynamics, stability analysis and practical efficiency demonstrated in diverse scenarios.

Basic Info
  • Host: GitHub
  • Owner: Rasoul-Zahedifar
  • License: mit
  • Language: MATLAB
  • Default Branch: main
  • Homepage:
  • Size: 326 KB
Statistics
  • Stars: 12
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

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Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Contributing
  5. License
  6. Contact
  7. Reference

About The Project

This research presents an innovative Lyapunov-based methodology for the dynamic formation control of Autonomous Underwater Vehicles (AUVs) while simultaneously tracking reference trajectories within a nonlinear dynamical system framework. The research commences by establishing the mathematical equations governing the AUV system. Subsequently, meticulously designed reference trajectories are generated for the leader AUV. To enable the leader robot to closely follow these trajectories, a feedback kinematic controller is introduced, ensuring asymptotic convergence. Further, a dynamic control law is devised to compute the requisite actuator torques for the leader AUV, facilitating effective maneuvering. A schematic of the block diagram of our design is depicted below.

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The investigation extends to the coordination of a group of AUVs through a formation control procedure. This procedure guarantees that the follower AUVs maintain a desired spatial configuration relative to the leader AUV while concurrently tracking the established reference trajectories. The stability analysis of the proposed method encompasses considerations for kinematic, dynamic, and formation controllers, employing the Lyapunov theory. The robustness and efficacy of the developed formation control algorithm are substantiated through a series of comprehensive case studies. These studies involve diverse formations, accounting for parametric uncertainties and external disturbances, providing conclusive evidence of the algorithm's effectiveness in tracking reference trajectories under varying conditions.

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Getting Started

In order to apply the codes, you may need to follow the steps below:

Prerequisites

You need to install MATLAB and Simulink Version 2017a or newer ones. If you are using an older version of MATLAB, please let me know at rasoul.zahedifar75@gmail.com to provide you with a save as compatible to your version.

Installation

You need to run the file "runner_simulation" in each case study. Please notice that the controller gains could be chosen in this file too.

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Usage

The old project is the version before the reviosion and the rest are after revision as the final versions. You can find different scenarios since they are named based on the number of the follower AUVs accordingly. You can find out about these scenarios as they are expressed completely in the paper of this research, titled same as this repository's title.

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again! 1. Fork the Project 2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`) 3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`) 4. Push to the Branch (`git push origin feature/AmazingFeature`) 5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Rasoul Zahedifar - rasoul.zahedifar75@gmail.com

Ali Keymasi Khalaji - keymasi@khu.ac.ir

GitHub Link: https://github.com/Rasoul-Zahedifar/Lyapunov-Based-Formation-Control-of-Underwater-Robots

Journal Link: https://www.cambridge.org/core/journals/robotica/lyapunovbased-formation-control-of-underwater-robots

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Reference

If you are interested in this work, please cite:

@ARTICLE{ authors={Keymasi Khalaji, Ali and Zahedifar, Rasoul}, journal={Robotica}, publisher={Cambridge University Press} title={Lyapunov-Based Formation Control of Underwater Robots}, year={2020}, volume={38}, issue={6}, pages={1105-1122}, doi={10.1017/S0263574719001279} }

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Owner

  • Name: Rasoul Zahedifar
  • Login: Rasoul-Zahedifar
  • Kind: user

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: Lyapunov-Based-Formation-Control-of-Underwater-Robots
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Ali
    family-names: Keymasi Khalaji
    email: keymasi@khu.ac.ir
    orcid: 'https://orcid.org/0000-0001-5414-6046'
  - given-names: Rasoul
    family-names: Zahedifar
    email: rasoul.zahedifar75@gmail.com
    orcid: 'https://orcid.org/0000-0002-7821-0185'
identifiers:
  - type: doi
    value: 10.1017/S0263574719001279
url: >-
  https://www.cambridge.org/core/journals/robotica/article/abs/lyapunovbased-formation-control-of-underwater-robots/EBBB0BBA1097C047541867FB61C197DC

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