Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach

<p dir="ltr">The problem of formation tracking control for a group of quadcopters with nonlinear dynamics using Barrier Lyapunov Functions (BLFs) is studied in this paper where the quadcopters are following a desired predefined trajectory in a predefined formation shape. The BLFs are...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Nargess Sadeghzadeh-Nokhodberiz (16904952) (author)
مؤلفون آخرون: Nader Meskin (14147796) (author)
منشور في: 2023
الموضوعات:
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
_version_ 1864513527064035328
author Nargess Sadeghzadeh-Nokhodberiz (16904952)
author2 Nader Meskin (14147796)
author2_role author
author_facet Nargess Sadeghzadeh-Nokhodberiz (16904952)
Nader Meskin (14147796)
author_role author
dc.creator.none.fl_str_mv Nargess Sadeghzadeh-Nokhodberiz (16904952)
Nader Meskin (14147796)
dc.date.none.fl_str_mv 2023-12-07T09:00:00Z
dc.identifier.none.fl_str_mv 10.1109/access.2023.3340417
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Consensus-Based_Distributed_Formation_Control_of_Multi-Quadcopter_Systems_Barrier_Lyapunov_Function_Approach/25239754
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Electrical engineering
Electronics, sensors and digital hardware
Materials engineering
Quadrotors
Formation control
Trajectory
Control systems
Consensus algorithm
Attitude control
Multi-robot systems
multi-quadcopter system
Barrier Lyapunov function (BLF)
dc.title.none.fl_str_mv Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">The problem of formation tracking control for a group of quadcopters with nonlinear dynamics using Barrier Lyapunov Functions (BLFs) is studied in this paper where the quadcopters are following a desired predefined trajectory in a predefined formation shape. The BLFs are employed to formulate the problem of formation trajectory tracking with a predefined accuracy. For this purpose, logarithmic BLFs including both the trajectory errors and the errors between the quadcopters’ distances with the desired ones (for the formation goal) are proposed. The method is firstly developed in a centralized scheme and then extended to a distributed framework using appropriate asymptotically convergent consensus algorithms. Therefore, the asymptotic convergence of the designed distributed algorithm to the centralized one is guaranteed. Moreover, due to the under-actuated feature of a quadcopter system, a general hierarchical scheme is considered for designing the controller. To this end, firstly a formation altitude tracking control is designed and then using the generated control signal, the formation translational tracking control is developed with the assumption of virtual inputs which are then employed to generate desired trajectory signals for the attitude control subsystem. Finally, attitude controllers are designed separately for each agent using the generated desired signals through logarithmic BLFs to consider a predefined accuracy. The efficiency of the proposed method is demonstrated through simulations and comparisons with the similar approaches in MATLAB-Simulink environment.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2023.3340417" target="_blank">https://dx.doi.org/10.1109/access.2023.3340417</a></p>
eu_rights_str_mv openAccess
id Manara2_7c711a8c3ce123c839d7d3e7ad0ab16b
identifier_str_mv 10.1109/access.2023.3340417
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/25239754
publishDate 2023
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function ApproachNargess Sadeghzadeh-Nokhodberiz (16904952)Nader Meskin (14147796)EngineeringElectrical engineeringElectronics, sensors and digital hardwareMaterials engineeringQuadrotorsFormation controlTrajectoryControl systemsConsensus algorithmAttitude controlMulti-robot systemsmulti-quadcopter systemBarrier Lyapunov function (BLF)<p dir="ltr">The problem of formation tracking control for a group of quadcopters with nonlinear dynamics using Barrier Lyapunov Functions (BLFs) is studied in this paper where the quadcopters are following a desired predefined trajectory in a predefined formation shape. The BLFs are employed to formulate the problem of formation trajectory tracking with a predefined accuracy. For this purpose, logarithmic BLFs including both the trajectory errors and the errors between the quadcopters’ distances with the desired ones (for the formation goal) are proposed. The method is firstly developed in a centralized scheme and then extended to a distributed framework using appropriate asymptotically convergent consensus algorithms. Therefore, the asymptotic convergence of the designed distributed algorithm to the centralized one is guaranteed. Moreover, due to the under-actuated feature of a quadcopter system, a general hierarchical scheme is considered for designing the controller. To this end, firstly a formation altitude tracking control is designed and then using the generated control signal, the formation translational tracking control is developed with the assumption of virtual inputs which are then employed to generate desired trajectory signals for the attitude control subsystem. Finally, attitude controllers are designed separately for each agent using the generated desired signals through logarithmic BLFs to consider a predefined accuracy. The efficiency of the proposed method is demonstrated through simulations and comparisons with the similar approaches in MATLAB-Simulink environment.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2023.3340417" target="_blank">https://dx.doi.org/10.1109/access.2023.3340417</a></p>2023-12-07T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2023.3340417https://figshare.com/articles/journal_contribution/Consensus-Based_Distributed_Formation_Control_of_Multi-Quadcopter_Systems_Barrier_Lyapunov_Function_Approach/25239754CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/252397542023-12-07T09:00:00Z
spellingShingle Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
Nargess Sadeghzadeh-Nokhodberiz (16904952)
Engineering
Electrical engineering
Electronics, sensors and digital hardware
Materials engineering
Quadrotors
Formation control
Trajectory
Control systems
Consensus algorithm
Attitude control
Multi-robot systems
multi-quadcopter system
Barrier Lyapunov function (BLF)
status_str publishedVersion
title Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
title_full Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
title_fullStr Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
title_full_unstemmed Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
title_short Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
title_sort Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
topic Engineering
Electrical engineering
Electronics, sensors and digital hardware
Materials engineering
Quadrotors
Formation control
Trajectory
Control systems
Consensus algorithm
Attitude control
Multi-robot systems
multi-quadcopter system
Barrier Lyapunov function (BLF)