2021
DOI: 10.1109/access.2021.3064883
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Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network

Abstract: In this paper, a sliding mode control based on neural networks is proposed for attitude and altitude system of quadcopter under external disturbances. First, the dynamic model of the quadcopter is considered under external disturbances. Sliding mode controllers are then integrated with neural network algorithm to achieve the time-varying sliding surface; their coefficients in sliding surface are adjusted through backpropagation law. The disturbance observer is also combined with sliding mode controllers to est… Show more

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Cited by 65 publications
(28 citation statements)
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References 35 publications
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“…Nguyen et al proposed a fault-tolerant control method based on adaptive, nonsingular fast terminal sliding mode control and neural network approximation for four-axis aircraft. In addition, an external disturbance sliding mode control method was proposed for the altitude attitude system [6]. Yang et al [7] used interval data to reduce the dimension of flight data and realized real-time prediction of UAV faults through a BP neural network.…”
Section: Literature Review 21 Data Driven Fault Analysis Methodsmentioning
confidence: 99%
“…Nguyen et al proposed a fault-tolerant control method based on adaptive, nonsingular fast terminal sliding mode control and neural network approximation for four-axis aircraft. In addition, an external disturbance sliding mode control method was proposed for the altitude attitude system [6]. Yang et al [7] used interval data to reduce the dimension of flight data and realized real-time prediction of UAV faults through a BP neural network.…”
Section: Literature Review 21 Data Driven Fault Analysis Methodsmentioning
confidence: 99%
“…Also, they used a novel time-varying sliding mode surface to eliminate the reaching phase, reduce the initial control effort, and meet the impact time requirement with a global sliding mode. In [32], sliding mode control was proposed based on the neural networks to stabilize the position and altitude of the quadcopter under external perturbations.…”
Section: Sliding Mode Algorithmmentioning
confidence: 99%
“…In Ref. [30], the fuzzy algorithm has been used to tackle parametric uncertainties and external disturbances. The reference [12] presents an adaptive SMC-fuzzy algorithm for trajectory tracking of the quadcopter.…”
Section: Introductionmentioning
confidence: 99%