Coordinated Control of UAV Swarm Using Multi Agent Control Scheme [Part II]

Almarri, Abdulaziz (2018) Coordinated Control of UAV Swarm Using Multi Agent Control Scheme [Part II]. [USQ Project]


Recently, unmanned aerial vehicles (UAVs) are being increasingly used in a variety of applications including commerce, entertainment and military sectors. In particular, the small size, cheap cost, increasing mission competence, and ability to be deployed in groups, has made this modern technology favorable for a variety of military applications including surveillance operations, destruction of opponent air defense, air support and accurate strike missions. However, the full potential of UAVs cannot be used without the adaptation of cooperative control strategies. In these schemes, a group of UAVs are coordinated so that they can form a specific arrangement. For instance, a swarm of UAVs can surround a target with a hexagonal formation. In this project, multi-agent cooperative control is used to solve the problem of formation control for UAV swarms. In this method, each UAV behaves as an autonomous agent, which takes actions based on limited amount of information about the neighbor UAVs. The acceleration of each UAV is controlled based on consensus protocol so as to ensure each UAV is attracted towards its assigned location within the formation graph. This way, the UAVs are aligned so as to form a desirable configuration (Ren and Sorensen, 2008). The proposed method is implemented using using C++ programming language. To test the efficacy of the algorithm under realistic conditions, the proposed control strategy is developed into a game, in which the user control the target so as to escape from the UAV swarm. On the other hand, the UAVs, which are controlled by displacement or distance based formation control algorithms, attempt to surround the moving target by perusing the formation of interest. This approach not only demonstrates the effectiveness of the proposed approach in realistic situations, but also avails the self-optimization. Consequently, the tactical mission can be completed with optimum accuracy.

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Item Type: USQ Project
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021)
Supervisors: Billingsley, John
Qualification: Bachelor of Engineering
Date Deposited: 01 Sep 2022 23:16
Last Modified: 27 Jun 2023 04:37
Uncontrolled Keywords: unmanned aerial vehicles (UAVs); coordinated

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