Tracking Formation Control for Multiple Quadrotors Based on Fuzzy Logic Controller and Least Square Oriented by Genetic Algorithm

Rabah, Abbas; Wu, Qinghe

doi:10.2174/1874444301507010842

Cited by 11 publications

(8 citation statements)

References 17 publications

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“…To ensure the robustness of quad-copter in the presence of disturbances and to solve the problem of formation control of multiple quad-rotors, many research efforts have been made. Abbas et al presented a leader-follower formation controller using classical proportional derivative scheme for tracking of leader on the desired trajectory and fuzzy logic system in order to achieve the desired formation pattern [12]. However, the uncertainties in the above controller were not taken into consideration.…”

Section: U Wmentioning

confidence: 99%

UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control

et al. 2021

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Leader follower formation of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has found numerous applications such as surveillance of critical infrastructure, industrial automation and disaster management emergency. For completion of high precision group tasks, the choice of appropriate control mechanism is of utmost importance. In presence of environmental effects,external disturbances and parametric uncertainties in the UAVs and UGV models, the controller design process is a challenging task. In order to address the aforementioned problems and to ensure minimum tracking errors and fast convergence of the states, this article proposes an adaptive robust formation and trajectory tracking control scheme for a leader follower formation of UAVs and UGV using Non-Singular Terminal Super Twisting Sliding Mode Control Method.Adaptive compensators are derived based on Lyapunov function method and stability of the proposed controllers is guaranteed. Two variants of the control schemes namely Adaptive Super Twisting SMC (AST-SMC) and Adaptive Non-Singular Terminal Super Twisting SMC (ANSTS-SMC) are tested using numerical simulations performed in MATLAB/Simulink. From the results presented, and with the proposed ANSTS-SMC control scheme, the measured [X , Y ] tracking errors for leader, follower1 and follower2 UAVs are [0 , 0.01]m,[0.01 , 0.02]m and [0.01 , 0.02]m respectively, While with the AST-SMC method the peak [X , Y ] tracking errors for leader, follower1 and follower2 UAVs are [0.05 , 0.05]m,[0.1 , 0.2]m and [0.05 , 0.1]m respectively. The proposed leader follower formation can be effectively used to monitor solar/PV panels and cables in large solar parks.

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Section: U Wmentioning

confidence: 99%

UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control

et al. 2021

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“…To solve the formation control problem of the quad rotor, many research efforts have been made. In [ 12 ] the authors proposed a leader–follower formation control using classical proportional derivative scheme and fuzzy logic system for the formation pattern. However the above controller did not take uncertainties into considerations.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Robust Trajectory Tracking Control of Multiple Quad-Rotor UAVs with Parametric Uncertainties and Disturbances

Mehmood¹,

Aslam²,

Ullah

et al. 2021

Sensors

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Recently, formation flying of multiple unmanned aerial vehicles (UAVs) found numerous applications in various areas such as surveillance, industrial automation and disaster management. The accuracy and reliability for performing group tasks by multiple UAVs is highly dependent on the applied control strategy. The formation and trajectories of multiple UAVs are governed by two separate controllers, namely formation and trajectory tracking controllers respectively. In presence of environmental effects, disturbances due to wind and parametric uncertainties, the controller design process is a challenging task. This article proposes a robust adaptive formation and trajectory tacking control of multiple quad-rotor UAVs using super twisting sliding mode control method. In the proposed design, Lyapunov function-based adaptive disturbance estimators are used to compensate for the effects of external disturbances and parametric uncertainties. The stability of the proposed controllers is guaranteed using Lyapunov theorems. Two variants of the control schemes, namely fixed gain super twisting SMC (STSMC) and adaptive super twisting SMC (ASTSMC) are tested using numerical simulations performed in MATLAB/Simulink. From the results presented, it is verified that in presence of disturbances, the proposed ASTSMC controller exhibits enhanced robustness as compared to the fixed gain STSMC.

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“…Geometric flight protocols were studied in literature. 7 In this work, a leader-follower configuration is used for a group of quadrotors. To achieve a desired formation in the XY plane, a fuzzy logic controller is used as coordination protocol.…”

Section: Introductionmentioning

confidence: 99%

A sectorial fuzzy consensus algorithm for the formation flight of multiple quadrotor unmanned aerial vehicles

Ollervides-Vazquez

Rojo-Rodriguez

Garcia‐Salazar

et al. 2020

International Journal of Micro Air Vehicles

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This paper presents an algorithm based on fuzzy theory for the formation flight of the multi-quadrotors. For this purpose, the mathematical model of N-quadrotor unmanned aerial vehicles is presented using the Newton-Euler formulation. The strategy of the formation flight is based on a structure composed by a sectorial fuzzy controller and the linear systems whose state variables are the position and velocity of the ith quadrotor. The stability analysis is described as a generalized form for N-quadrotor unmanned aerial vehicles and it is based on the Lyapunov theory. This analysis demonstrates that the closed-loop system is globally asymptotically stable so that the quadrotors unmanned aerial vehicles reach the consensus. Numerical simulation demonstrates the robustness of the proposed scheme for the formation flight even in the presence of disturbances. Finally, experimental results show the feasibility of the proposed algorithm for the formation flight of multiple unmanned aerial vehicles.

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Tracking Formation Control for Multiple Quadrotors Based on Fuzzy Logic Controller and Least Square Oriented by Genetic Algorithm

Cited by 11 publications

References 17 publications

UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control

UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control

Adaptive Robust Trajectory Tracking Control of Multiple Quad-Rotor UAVs with Parametric Uncertainties and Disturbances

A sectorial fuzzy consensus algorithm for the formation flight of multiple quadrotor unmanned aerial vehicles

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