Robust Fault Estimation Using the Intermediate Observer: Application to the Quadcopter

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 estimate and handle the external disturbances. Finally, the Lyapunov theory is applied to validate the stability of suggested control method. The performance of proposed sliding mode control has been evaluated using a numerical simulation. The results show that the attitude and altitude controller based on suggested algorithm has a better tracking performance and disturbance rejection.

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“…x y z . The nonlinear dynamic equations of the quadcopter in presence of disturbances and uncertainties can be expressed as follows [33,34]…”

Section: Mathematical Model Of Quadcoptermentioning

confidence: 99%

Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network

et al. 2021

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“…The sensor fault interferes with the stability of the system and affects the judgment of the operator, which may lead to fault. Therefore, it is very important to diagnose process faults and sensor faults in modern industrial processes [ 7 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Integrated Diagnostic Framework for Process and Sensor Faults in Chemical Industry

Zhang

Luo

Dai

2021

Sensors

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This study considers the problem of distinguishing between process and sensor faults in nonlinear chemical processes. An integrated fault diagnosis framework is proposed to distinguish chemical process sensor faults from process faults. The key idea of the framework is to embed the cycle temporal algorithm into the dynamic kernel principal component analysis to improve the fault detection speed and accuracy. It is combined with the fault diagnosis method based on the reconstruction-based contribution graph to diagnose the fault variables and then distinguish the two fault types according to their characteristics. Finally, the integrated fault diagnosis framework is applied to the Tennessee Eastman process and acid gas absorption process, and its effectiveness is proved.

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“…U NMANNED aerial vehicles UAVs have become increasingly popular in recent years. Aerial images and videos captured by UAVs are widely utilized in various fields, such as surveillance [1], [2], forest and agriculture monitoring [3], [4], weather forecasting [5], and geographic mapping [6].…”

Section: Introductionmentioning

confidence: 99%

Fast and Efficient Method for Large-Scale Aerial Image Stitching

Pham¹,

Park

2021

IEEE Access

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Recent studies on image stitching have been extensively conducted to stitch panoramic or 360 • images using a small number of input images. The stitching of aerial images, that are captured by unmanned aerial vehicles (UAVs), has various practical applications. In this paper, we propose a fast adaptive stitching algorithm for handling numerous aerial images. First, the proposed method analyzes the relative positions and overlapping regions of the UAV image footprints by exploiting their geotag information. Based on the analysis, an adaptive selection algorithm is proposed to eliminate the densely overlapped images from among all the UAV images. Then, the proposed method sequentially performs fast feature extraction and feature matching. Finally, a local warp method, with a smooth transition for overlapping regions, is introduced to alleviate the blurring artifacts and achieve highly accurate image alignment. The experiments are conducted for various scenarios to generate seamless terrestrial mosaic images of large areas. The proposed method improves the visual quality of the stitched image, by decreasing the estimated reprojection error and the number of observed visual distortions. In addition, the proposed method can substantially reduce the processing time compared with conventional stitching methods.

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Robust Fault Estimation Using the Intermediate Observer: Application to the Quadcopter

Cited by 13 publications

References 28 publications

Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network

Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network

Integrated Diagnostic Framework for Process and Sensor Faults in Chemical Industry

Fast and Efficient Method for Large-Scale Aerial Image Stitching

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