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You searched for subject:(Flocking AND consensus algorithms). Showing records 1 – 8 of 8 total matches.

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Arizona State University

1. Theisen, Ryan. Convergence Results for Two Models of Interaction.

Degree: Mathematics, 2018, Arizona State University

 I investigate two models interacting agent systems: the first is motivated by the flocking and swarming behaviors in biological systems, while the second models opinion… (more)

Subjects/Keywords: Applied mathematics; Consensus; Dynamical systems; Flocking; Swarming

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APA (6th Edition):

Theisen, R. (2018). Convergence Results for Two Models of Interaction. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/51785

Chicago Manual of Style (16th Edition):

Theisen, Ryan. “Convergence Results for Two Models of Interaction.” 2018. Masters Thesis, Arizona State University. Accessed November 22, 2019. http://repository.asu.edu/items/51785.

MLA Handbook (7th Edition):

Theisen, Ryan. “Convergence Results for Two Models of Interaction.” 2018. Web. 22 Nov 2019.

Vancouver:

Theisen R. Convergence Results for Two Models of Interaction. [Internet] [Masters thesis]. Arizona State University; 2018. [cited 2019 Nov 22]. Available from: http://repository.asu.edu/items/51785.

Council of Science Editors:

Theisen R. Convergence Results for Two Models of Interaction. [Masters Thesis]. Arizona State University; 2018. Available from: http://repository.asu.edu/items/51785

2. Saif, Osamah. Reactive navigation of a fleet of drones in interaction : Navigation réactive de drones en interaction dans une flottille.

Degree: Docteur es, Technologies de l'Information et des Systèmes, 2016, Compiègne

De nos jours, les applications utilisant des quadrirotors autonomes sont en plein essor. La surveillance et la sécurité de sites industriels ou sensibles, de zones… (more)

Subjects/Keywords: Commande de vol en formation; Flocking et algorithmes de consensus; Commande LQR; Commande comportementale; Véhicules aériens sans pilote (UAV); Quadrirotors; Flight formation control; Flocking and consensus algorithms; LQR control; Behavioral-based control; Unmanned Aerial Vehicles (UAV)

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APA (6th Edition):

Saif, O. (2016). Reactive navigation of a fleet of drones in interaction : Navigation réactive de drones en interaction dans une flottille. (Doctoral Dissertation). Compiègne. Retrieved from http://www.theses.fr/2016COMP2269

Chicago Manual of Style (16th Edition):

Saif, Osamah. “Reactive navigation of a fleet of drones in interaction : Navigation réactive de drones en interaction dans une flottille.” 2016. Doctoral Dissertation, Compiègne. Accessed November 22, 2019. http://www.theses.fr/2016COMP2269.

MLA Handbook (7th Edition):

Saif, Osamah. “Reactive navigation of a fleet of drones in interaction : Navigation réactive de drones en interaction dans une flottille.” 2016. Web. 22 Nov 2019.

Vancouver:

Saif O. Reactive navigation of a fleet of drones in interaction : Navigation réactive de drones en interaction dans une flottille. [Internet] [Doctoral dissertation]. Compiègne; 2016. [cited 2019 Nov 22]. Available from: http://www.theses.fr/2016COMP2269.

Council of Science Editors:

Saif O. Reactive navigation of a fleet of drones in interaction : Navigation réactive de drones en interaction dans une flottille. [Doctoral Dissertation]. Compiègne; 2016. Available from: http://www.theses.fr/2016COMP2269


Université de Grenoble

3. Martin, Samuel. Coordination et robustesse des systèmes dynamiques multi-agents : Coordination and robustness in dynamical multi-agents systems.

Degree: Docteur es, Mathématiques Appliquées, 2012, Université de Grenoble

Nous nous intéressons à l'étude de la dynamique des réseaux composés d'une multitude d'agents. Les motivations de ce travail trouvent leurs sources dans de nombreux… (more)

Subjects/Keywords: Robustesse; Consensus; Flocking; Analyse de réseaux sociaux; Systèmes dynamiques multi-agents; Coordination; Robustness; Consensus; Flocking; Social network analysis; Dynamical multi-agents systems; Coordination

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APA (6th Edition):

Martin, S. (2012). Coordination et robustesse des systèmes dynamiques multi-agents : Coordination and robustness in dynamical multi-agents systems. (Doctoral Dissertation). Université de Grenoble. Retrieved from http://www.theses.fr/2012GRENM101

Chicago Manual of Style (16th Edition):

Martin, Samuel. “Coordination et robustesse des systèmes dynamiques multi-agents : Coordination and robustness in dynamical multi-agents systems.” 2012. Doctoral Dissertation, Université de Grenoble. Accessed November 22, 2019. http://www.theses.fr/2012GRENM101.

MLA Handbook (7th Edition):

Martin, Samuel. “Coordination et robustesse des systèmes dynamiques multi-agents : Coordination and robustness in dynamical multi-agents systems.” 2012. Web. 22 Nov 2019.

Vancouver:

Martin S. Coordination et robustesse des systèmes dynamiques multi-agents : Coordination and robustness in dynamical multi-agents systems. [Internet] [Doctoral dissertation]. Université de Grenoble; 2012. [cited 2019 Nov 22]. Available from: http://www.theses.fr/2012GRENM101.

Council of Science Editors:

Martin S. Coordination et robustesse des systèmes dynamiques multi-agents : Coordination and robustness in dynamical multi-agents systems. [Doctoral Dissertation]. Université de Grenoble; 2012. Available from: http://www.theses.fr/2012GRENM101


Université de Lorraine

4. Belkadi, Adel. Conception de commande tolérante aux défauts pour les systèmes multi-agents : application au vol en formation d'une flotte de véhicules autonomes aériens : FDI/FT Methods Design to multi-agent systems : Application to formation control of a fleet of autonomous aerial vehicles.

Degree: Docteur es, Automatique, Traitement du signal et des images, Génie informatique, 2017, Université de Lorraine

Ces dernières années, l’émergence des nouvelles technologies tels que la miniaturisation des composants, les dispositifs de communication sans fils, l’augmentation de la taille de stockage… (more)

Subjects/Keywords: Commande de flotte; Flocking; Algorithme de consensus; PSO; Optimisation; Méta-heuristique; Quadrirotors; Commande distribuée; Fleet control; Flocking; Consensus algorithm; PSO; Optimization; Méta-heuristics; Quadrotors; Distributed control; 629.892 63

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APA (6th Edition):

Belkadi, A. (2017). Conception de commande tolérante aux défauts pour les systèmes multi-agents : application au vol en formation d'une flotte de véhicules autonomes aériens : FDI/FT Methods Design to multi-agent systems : Application to formation control of a fleet of autonomous aerial vehicles. (Doctoral Dissertation). Université de Lorraine. Retrieved from http://www.theses.fr/2017LORR0183

Chicago Manual of Style (16th Edition):

Belkadi, Adel. “Conception de commande tolérante aux défauts pour les systèmes multi-agents : application au vol en formation d'une flotte de véhicules autonomes aériens : FDI/FT Methods Design to multi-agent systems : Application to formation control of a fleet of autonomous aerial vehicles.” 2017. Doctoral Dissertation, Université de Lorraine. Accessed November 22, 2019. http://www.theses.fr/2017LORR0183.

MLA Handbook (7th Edition):

Belkadi, Adel. “Conception de commande tolérante aux défauts pour les systèmes multi-agents : application au vol en formation d'une flotte de véhicules autonomes aériens : FDI/FT Methods Design to multi-agent systems : Application to formation control of a fleet of autonomous aerial vehicles.” 2017. Web. 22 Nov 2019.

Vancouver:

Belkadi A. Conception de commande tolérante aux défauts pour les systèmes multi-agents : application au vol en formation d'une flotte de véhicules autonomes aériens : FDI/FT Methods Design to multi-agent systems : Application to formation control of a fleet of autonomous aerial vehicles. [Internet] [Doctoral dissertation]. Université de Lorraine; 2017. [cited 2019 Nov 22]. Available from: http://www.theses.fr/2017LORR0183.

Council of Science Editors:

Belkadi A. Conception de commande tolérante aux défauts pour les systèmes multi-agents : application au vol en formation d'une flotte de véhicules autonomes aériens : FDI/FT Methods Design to multi-agent systems : Application to formation control of a fleet of autonomous aerial vehicles. [Doctoral Dissertation]. Université de Lorraine; 2017. Available from: http://www.theses.fr/2017LORR0183


NSYSU

5. Lin, Chih-Yu. Adaptive Flocking Algorithm with Range Coverage for Target Tracking in Mobile Sensor Networks.

Degree: Master, Electrical Engineering, 2011, NSYSU

 The accuracy of target location and the coverage range of sensor network are two factors that affect each other in target tracking. When the flocking(more)

Subjects/Keywords: cost function; Kalman-consensus information filter; flocking algorithm; target tracking; network coverage

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APA (6th Edition):

Lin, C. (2011). Adaptive Flocking Algorithm with Range Coverage for Target Tracking in Mobile Sensor Networks. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0831111-202102

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lin, Chih-Yu. “Adaptive Flocking Algorithm with Range Coverage for Target Tracking in Mobile Sensor Networks.” 2011. Thesis, NSYSU. Accessed November 22, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0831111-202102.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lin, Chih-Yu. “Adaptive Flocking Algorithm with Range Coverage for Target Tracking in Mobile Sensor Networks.” 2011. Web. 22 Nov 2019.

Vancouver:

Lin C. Adaptive Flocking Algorithm with Range Coverage for Target Tracking in Mobile Sensor Networks. [Internet] [Thesis]. NSYSU; 2011. [cited 2019 Nov 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0831111-202102.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin C. Adaptive Flocking Algorithm with Range Coverage for Target Tracking in Mobile Sensor Networks. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0831111-202102

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

6. Young, George Forrest. Optimising Robustness of Consensus to Noise on Directed Networks .

Degree: PhD, 2014, Princeton University

 A major area of study in recent years has been the development of robotic groups that are capable of carrying out complicated and useful tasks… (more)

Subjects/Keywords: Collective Behaviour; Consensus; Flocking; Graph Theory; Networks; Robust Control

…Introduction 1 1.1 Robust Consensus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4… …Bird Flocking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 Outline… …2.2 Linear Consensus Dynamics . . . . . . . . . . . . . . . . . . . . . . . 16 2.3… …Theory . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3 Robustness of Consensus to… …Noise 33 3.1 Noisy Consensus Dynamics . . . . . . . . . . . . . . . . . . . . . . . . 33… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7 Sample image

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APA (6th Edition):

Young, G. F. (2014). Optimising Robustness of Consensus to Noise on Directed Networks . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01z029p486t

Chicago Manual of Style (16th Edition):

Young, George Forrest. “Optimising Robustness of Consensus to Noise on Directed Networks .” 2014. Doctoral Dissertation, Princeton University. Accessed November 22, 2019. http://arks.princeton.edu/ark:/88435/dsp01z029p486t.

MLA Handbook (7th Edition):

Young, George Forrest. “Optimising Robustness of Consensus to Noise on Directed Networks .” 2014. Web. 22 Nov 2019.

Vancouver:

Young GF. Optimising Robustness of Consensus to Noise on Directed Networks . [Internet] [Doctoral dissertation]. Princeton University; 2014. [cited 2019 Nov 22]. Available from: http://arks.princeton.edu/ark:/88435/dsp01z029p486t.

Council of Science Editors:

Young GF. Optimising Robustness of Consensus to Noise on Directed Networks . [Doctoral Dissertation]. Princeton University; 2014. Available from: http://arks.princeton.edu/ark:/88435/dsp01z029p486t

7. Wang, Jianan. MULTI-AGENT COOPERATIVE CONTROL VIA A UNIFIED OPTIMAL CONTROL APPROACH.

Degree: PhD, Aerospace Engineering, 2011, Mississippi State University

  Recent rapid advances in computing, communication, sensing, and actuation, together with miniaturization technologies, have offered unprecedented opportunities to employ large numbers of autonomous vehicles… (more)

Subjects/Keywords: formation control; flocking; Multi-agent system; cooperative control; consensus; inverse optimal control; rendezvous

…group of researchers designed different consensus algorithms for the double-integrator… …theoretical framework for the design and analysis of distributed flocking algorithms was introduced… …in [138]. Two resulting flocking algorithms were given under the obstacle-free… …Consensus algorithms from the optimal control perspective have been explored from two aspects: 1… …Optimal consensus ...............................................................3 1.2.1.2… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, J. (2011). MULTI-AGENT COOPERATIVE CONTROL VIA A UNIFIED OPTIMAL CONTROL APPROACH. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-11032011-144900/ ;

Chicago Manual of Style (16th Edition):

Wang, Jianan. “MULTI-AGENT COOPERATIVE CONTROL VIA A UNIFIED OPTIMAL CONTROL APPROACH.” 2011. Doctoral Dissertation, Mississippi State University. Accessed November 22, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-11032011-144900/ ;.

MLA Handbook (7th Edition):

Wang, Jianan. “MULTI-AGENT COOPERATIVE CONTROL VIA A UNIFIED OPTIMAL CONTROL APPROACH.” 2011. Web. 22 Nov 2019.

Vancouver:

Wang J. MULTI-AGENT COOPERATIVE CONTROL VIA A UNIFIED OPTIMAL CONTROL APPROACH. [Internet] [Doctoral dissertation]. Mississippi State University; 2011. [cited 2019 Nov 22]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-11032011-144900/ ;.

Council of Science Editors:

Wang J. MULTI-AGENT COOPERATIVE CONTROL VIA A UNIFIED OPTIMAL CONTROL APPROACH. [Doctoral Dissertation]. Mississippi State University; 2011. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-11032011-144900/ ;

8. Wellman, Brandon. ADVANCES IN MULTI-AGENT FLOCKING: CONTINUOUS-TIME AND DISCRETE-TIME ALGORITHMS.

Degree: 2017, University of Kentucky

 We present multi-agent control methods that address flocking in continuous-time and discrete-time settings. The method is decentralized, that is, each agents controller relies on local… (more)

Subjects/Keywords: flocking; multi-agent system; consensus algorithm; quadcopter; formation control; sampled-data control; motion-capture system; Acoustics, Dynamics, and Controls; Controls and Control Theory

…to platoons of vehicles [15]. Flocking algorithms 2 derive their name from… …Flocking algorithms generalize birds to a broad range of vehicles such as cars, rotorcraft… …configuration. The three characteristics of flocking are collision avoidance, velocity consensus, and… …to be close to another. Flocking algorithms induce formations of vehicles in which the… …compressed formation around the leader. Consensus algorithms [17, 34–56] can be used for… 

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APA (6th Edition):

Wellman, B. (2017). ADVANCES IN MULTI-AGENT FLOCKING: CONTINUOUS-TIME AND DISCRETE-TIME ALGORITHMS. (Doctoral Dissertation). University of Kentucky. Retrieved from https://uknowledge.uky.edu/me_etds/99

Chicago Manual of Style (16th Edition):

Wellman, Brandon. “ADVANCES IN MULTI-AGENT FLOCKING: CONTINUOUS-TIME AND DISCRETE-TIME ALGORITHMS.” 2017. Doctoral Dissertation, University of Kentucky. Accessed November 22, 2019. https://uknowledge.uky.edu/me_etds/99.

MLA Handbook (7th Edition):

Wellman, Brandon. “ADVANCES IN MULTI-AGENT FLOCKING: CONTINUOUS-TIME AND DISCRETE-TIME ALGORITHMS.” 2017. Web. 22 Nov 2019.

Vancouver:

Wellman B. ADVANCES IN MULTI-AGENT FLOCKING: CONTINUOUS-TIME AND DISCRETE-TIME ALGORITHMS. [Internet] [Doctoral dissertation]. University of Kentucky; 2017. [cited 2019 Nov 22]. Available from: https://uknowledge.uky.edu/me_etds/99.

Council of Science Editors:

Wellman B. ADVANCES IN MULTI-AGENT FLOCKING: CONTINUOUS-TIME AND DISCRETE-TIME ALGORITHMS. [Doctoral Dissertation]. University of Kentucky; 2017. Available from: https://uknowledge.uky.edu/me_etds/99

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