A Novel Integrated Guidance and Control System Design in Formation Flight

Sadeghi, Mohammad; Abaspour, Alireza; Sadati, Seyed Hossein

doi:10.5028/jatm.v7i4.473

Cited by 12 publications

(4 citation statements)

References 19 publications

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“…To achieve these types of applications, UAVs may need to flying near each other with a specific structure. Formation flight control is one of the most straightforward cooperative strategies which consists of a set of aircraft flying near to each other in a defined distance [37].…”

Section: Military Applicationsmentioning

confidence: 99%

See 1 more Smart Citation

Control of Cooperative Unmanned Aerial Vehicles: Review of Applications, Challenges, and Algorithms

Sargolzaei¹,

Abbaspour²,

Crane³

2019

Preprint

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A system of cooperative unmanned aerial vehicles (UAVs) is a group of agents interacting with each other and the surrounding environment to achieve a specific task. In contrast with a single UAV, UAV swarms are expected to benefit efficiency, flexibility, accuracy, robustness, and reliability. However, the provision of external communications potentially exposes them to an additional layer of faults, failures, uncertainties, and cyber-attacks and can contribute to the propagation of error from one component to other components in a network. Also, other challenges such as complex nonlinear dynamic of UAVs, collision avoidance, velocity matching, and cohesion should be addressed adequately. Main applications of cooperative UAVs are border patrol; search and rescue; surveillance; mapping; military. Challenges to be addressed in decision and control in cooperative systems may include the complex nonlinear dynamic of UAVs, collision avoidance, velocity matching, and cohesion. In this paper, emerging topics in the field of cooperative UAVs control and their associated practical approaches are reviewed.

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Section: Military Applicationsmentioning

confidence: 99%

“…Thus, we discussed the PP guidance laws application in the control design of the flight formation systems. integrating the guidance and control system through a PID control design [37]. Their proposed approach could improve the PP guidance algorithm accuracy and the maneuverability of the formation group.…”

Section: Guidance-law Based Cooperative Controlmentioning

confidence: 99%

Control of Cooperative Unmanned Aerial Vehicles: Review of Applications, Challenges, and Algorithms

Sargolzaei¹,

Abbaspour²,

Crane³

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…The Unmanned Aerial Vehicle (UAV) swarm technology has seen tremendous development due to its applications in civil and military applications, such as surveillance [1,2], search and rescue [3][4][5], fire-fighting and combat operations [6,7]. The UAV has limited potential due to its limited search range and load capacity.…”

Section: Introductionmentioning

confidence: 99%

Offense-Defense Distributed Decision Making for Swarm vs. Swarm Confrontation While Attacking the Aircraft Carriers

Shahid

Zhen

Javaid

et al. 2022

Drones

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The effectiveness of multiple UAVs at attacking the enemy target and defending against the attacking UAVs simultaneously gained researchers’ attention due to their cost efficiency and high mission success rates. This paper explores the UAV swarm vs. swarm offense/defense confrontation decision-making while attacking the aircraft carriers on open seas. The system is developed as a multi-agent system. Precisely, every UAV is modeled as an independent agent, which is free to make decisions based on the behavioral rules of the swarm, detection radius, and enemy location. A distributed auction-based algorithm with a limited data-sharing rate ability is formulated among swarm UAVs. A critical feature of the proposed strategy is that it empowers each UAV to make decisions in real-time during the mission in the presence of relatively limited communication hardware in terms of the update rate within the UAV communication system. The algorithm parameters are optimized to obtain an improved target allocation and elimination. Simulation results are presented to show the effectiveness of the proposed Offence-Defense UAV-based swarm Strategy.

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“…Formation flight has various applications in mapping, search and rescue, and surveillance [29][30][31][32]. Several methods can be used for the formation flight control like leader-follower [33,34], pure pursuit [35], and virtual structure [36].…”

mentioning

confidence: 99%

Robust Nonlinear Fuzzy Formation Control of Unmanned Quadrotors

Khakshour¹,

Nourani²

2017

IJCA

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A novel leader-following strategy based on fuzzy logic is introduced to design a formation flight controller for unmanned quadrotors. The proposed strategy uses particle swarm optimization (PSO) to optimize the fuzzy membership function in the guidance law, and a nonlinear dynamic inversion (NDI) controller is designed to control the nonlinear dynamics of the quadrotor. The simulation results show the proposed method has significant advantages in comparison with conventional leading-following strategies in terms of robustness against wind gusts, uncertainties, and unknown dynamics.

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A Novel Integrated Guidance and Control System Design in Formation Flight

Cited by 12 publications

References 19 publications

Control of Cooperative Unmanned Aerial Vehicles: Review of Applications, Challenges, and Algorithms

Control of Cooperative Unmanned Aerial Vehicles: Review of Applications, Challenges, and Algorithms

Offense-Defense Distributed Decision Making for Swarm vs. Swarm Confrontation While Attacking the Aircraft Carriers

Robust Nonlinear Fuzzy Formation Control of Unmanned Quadrotors

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