2022
DOI: 10.1016/j.compeleceng.2022.108299
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A finite time composite control method for quadrotor UAV with wind disturbance rejection

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Cited by 12 publications
(17 citation statements)
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“…Figure 3(a) shows the state response curves of the six-rotor UAV in the conventional perturbed environment without fault, where the disturbance models are shown as equations ( 51), ( 52), (53), and (54). Figure 3(b) shows the simulation diagram in the presence of wind disturbance, in which the wind disturbance model is used in Shenghui et al (2022), and the wind disturbance is set to exist in 0-15 s…”
Section: Simulation Results and Analysismentioning
confidence: 99%
“…Figure 3(a) shows the state response curves of the six-rotor UAV in the conventional perturbed environment without fault, where the disturbance models are shown as equations ( 51), ( 52), (53), and (54). Figure 3(b) shows the simulation diagram in the presence of wind disturbance, in which the wind disturbance model is used in Shenghui et al (2022), and the wind disturbance is set to exist in 0-15 s…”
Section: Simulation Results and Analysismentioning
confidence: 99%
“…To enhance the wind disturbance resistance performance of quadrotor, [26] effectively combined the ESO and the DOB, and proposed a compound observer method. In [27], a wind-disturbance strategy based on proportional-integral observer was designed for UAV. In [28], an adaptive controller was proposed on the basis of a sliding mode observer, and an experimental platform was built using an ultra-wideband sensor to conduct trajectory tracking experiments in an outdoor gust environment.…”
Section: Introductionmentioning
confidence: 99%
“…However, in the above research, the designed controller can only guarantee asymptotic convergence [14-16, 25, 26] or finite time convergence [17,27,28]. The concept of asymptotic convergence implies that the convergence time is infinite, and finite time convergence is affected by the initial value.…”
Section: Introductionmentioning
confidence: 99%
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“…The quadrotor UAV has a smaller geometric size and a lighter mass, which makes it more sensitive to wind disturbances. Considering that the quadrotor UAV usually suffers external disturbances in actual flight, such as wind gust and turbulent fluid flow [35–37], it is necessary to design a controller with anti‐disturbance and high precision. Schiano et al [38] built a quadrotor UAV system model in the wind field environment, added an integral term on the basis of LQR control algorithm to improve the anti‐disturbance ability of the quadrotor UAV, and conducted experiments in the wind tunnel to verify the accuracy of the model and the effectiveness of the controller.…”
Section: Introductionmentioning
confidence: 99%