An approach to surveillance an area using swarm of fixed wing and quad-rotor unmanned aerial vehicles UAV(s)

Jaimes, Aldo; Kota, S.; Gómez, José Luís Graña

doi:10.1109/sysose.2008.4724195

Cited by 68 publications

(33 citation statements)

References 5 publications

(1 reference statement)

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“…Much of the current research into these multi-UAV swarms focuses on quad-rotor UAVs, but a number of research efforts are specifically directed at outdoor field experimentation with systems of fixed-wing vehicles. By necessity, many of these research efforts have emphasized platform development [1], [2], [3], use cases [4], [5], and control algorithms for coordinated behaviors [6], [7], [8]. As the numbers of coordinating UAVs has increased, however, additional factors affecting UAV swarms have received increasing attention including human factors associated with control of large swarms [9], [10], logistical aspects of maintaining and deploying these systems [11], and multi-vehicle coordination in the face of communications limits [12], [13].…”

Section: Introductionmentioning

confidence: 99%

Consensus-based data sharing for large-scale aerial swarm coordination in lossy communications environments

Davis

Chung

Clement

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-Increasing unmanned aerial vehicle (UAV) capabilities and decreasing costs have facilitated growing interest in the development of large, multi-UAV systems, or swarms. The constrained communications environments in which these swarms operate, however, have limited the development of behaviors that require a high degree of deliberative coordination. This work presents two algorithms that use a consensusalgorithm approach to reliably exchange information throughout large swarms as a means of facilitating swarm behavior coordination. Results from experiments conducted in simulation and live-fly exercises are presented and discussed.

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Section: Introductionmentioning

confidence: 99%

Consensus-based data sharing for large-scale aerial swarm coordination in lossy communications environments

Davis

Chung

Clement

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…Quad-rotors possess tremendous advantages over other types of UAVs in terms of manoeuvring capability, safety, weight, and cost. It can be used for applications such as search and rescue, surveillance, and remote inspection (Jaimes et al, 2008). One of the challenges when constructing this type of vehicles is the stabilisation problem with dynamic changes in the model parameters.…”

Section: Introductionmentioning

confidence: 99%

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

Vial

Dong

Alshbatat

2016

IJISTA

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It is challenging to stabilise an unmanned quad-rotor aerial vehicle when a dynamic change in its model parameters or failure of its actuator occurs. In this paper, a quad-rotor unmanned aerial vehicle (UAV) is controlled based on model reference adaptive control (MRAC) and a linear quadratic regulator (LQR). The kinematics and dynamics of the quad-rotor are calculated, and Lyapunov's direct stability method is used to design the MRAC. In order to evaluate the performance of the adaptive control algorithms in the presence of thrust loss that may occur due to component failure or physical damage, a real quad-rotor is built from scratch using commercial components. Both controllers are designed, implemented and tested using AVR microcontrollers. Comparison is made between the controllers under normal and faulty situations and the effectiveness of the proposed control strategy is verified. Simulation and experimental results show that both controllers have satisfactory performance under normal conditions and even in the presence of the partial loss of thrust that may occur due to the loss of control effectiveness in one of the rotors or the damage of one propeller, superior system performance is observed using the proposed MRAC controller.

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“…Quadrotors can be used to perform several tasks in the applications of dangerous area for a manned aircraft in a high level of accuracy. It can be used in different applications, such as inspection of power lines, oil platforms, search and rescue operations, and surveillance [4] [5]. Control of a quadrotor helicopter is a challenging task.…”

Section: Introductionmentioning

confidence: 99%

H<inf>∞</inf> for quadrotor attitude stabilization

Jasim

2014

2014 UKACC International Conference on Control (CONTROL)

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This paper proposes a state feedback controller for the attitude stabilization problem of quadrotors. The quadrotor attitude is represented by unit quaternion and disturbance of the attitude model is taken into consideration. A robust controller is synthesized via H∞ optimal design approach. Solving the nonlinear H∞ optimal control problem using state feedback is meltdown to finding a solution to a Hamilton-Jacobi inequality. Based on the quadrotor attitude dynamics, an appropriate parameterized Lyapunov function is selected and the corresponding state feedback controller is derived. Then the parameters are found from a Hamilton-Jacobi inequality. The resultant state feedback controller can lead to closed-loop nonlinear system having L2-gain less than or equal to a constant γ, and establish the asymptotically stability of the closed-loop nonlinear system without external disturbance. The simulation provides the results to show the stability and the robust performance against to disturbance. I. INTRODUCTIONIn recent years, research in control of Quadrotor has been growing due to its simplicity in design and low cost. Quadrotors have several advantages over fixed-wing aircrafts, such as take-off and landing vertically in a limit space, easy hover over fixed or dynamic targets, which give them efficiency in applications that fixed-wing aircrafts cannot do, and they are safer [1][2] [3]. Quadrotors can be used to perform several tasks in the applications of dangerous area for a manned aircraft in a high level of accuracy. It can be used in different applications, such as inspection of power lines, oil platforms, search and rescue operations, and surveillance [4] [5]. Control of a quadrotor helicopter is a challenging task. The difficulty comes from the complexity of modeling its dynamic system, their underactuated mechanism, and various external disturbances [5] [6].The attitude control is to stabilize the orientation of quadrotors, which is a first step towards more complex control systems [5]. Researchers have been focusing on design and implementation of many types of controller to control the attitude of individual quadrotors. A nonlinear proportional squared control algorithm was proposed in [7] for attitude control. The controller was implemented to a linear quaternion simulator of quadrotors. Elias R. et al.[8] presented a nonlinear quaternion mathematical model to describe the attitude dynamics of quadrotors. They implemented a LQR gain scheduling controller for trajectory tracking and attitude stability tasks. A bounded control law was presented to obtain

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An approach to surveillance an area using swarm of fixed wing and quad-rotor unmanned aerial vehicles UAV(s)

Cited by 68 publications

References 5 publications

Consensus-based data sharing for large-scale aerial swarm coordination in lossy communications environments

Consensus-based data sharing for large-scale aerial swarm coordination in lossy communications environments

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

H<inf>∞</inf> for quadrotor attitude stabilization

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An approach to surveillance an area using swarm of fixed wing and quad-rotor unmanned aerial vehicles UAV(s)

Cited by 68 publications

References 5 publications

Consensus-based data sharing for large-scale aerial swarm coordination in lossy communications environments

Consensus-based data sharing for large-scale aerial swarm coordination in lossy communications environments

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

H<inf>&#x221E;</inf> for quadrotor attitude stabilization

Contact Info

Product

Resources

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H<inf>∞</inf> for quadrotor attitude stabilization