Adaptive Nonlinear Controller for the Trajectory Tracking of the Quadrotor with Uncertainties

Benaddy, Abdellah; Labbadi, Moussa; Bouzi, Mostafa

doi:10.1109/gpecom49333.2020.9247922

Cited by 7 publications

(3 citation statements)

References 14 publications

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“…The earthfixed frame and the body frames are represented by E = [x e , y e , z e ] T and B = [x b , y b , z b ] T , respectively. The quadrotor dynamics can be expressed using the Newton-Euler formalism as follows [7,33].…”

Section: Problem Formulationmentioning

confidence: 99%

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Predefined-Time Fractional-Order Tracking Control for UAVs with Perturbation

Benaddy,

Labbadi,

Boubaker

et al. 2023

Mathematics

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This manuscript describes the design of a controller that assures predefined-time convergence in fractional-order sliding mode control (PTFOSMC) for a quadrotor UAV subjected to matched perturbation. Moreover, predefined-time techniques enable the establishment of a time constraint for convergence as a control parameter, distinguishing them from finite- and fixed-time controllers. The proposed control offers the advantage of sliding mode control, exhibiting rapid response and robust performance for the quadrotor subsystems. Notably, the suggested controller is devoid of terms dependent on the initial conditions of the quadrotor. Additionally, an established switching-type predefined-time controller with fractional-order is introduced to bolster robustness against external disturbances and alleviate the chattering problem associated with the sliding mode technique. The application of the Lyapunov function is employed to analyze the predefined-time stability of the quadrotor utilizing the suggested PTFOSMC. Numerical results are provided to demonstrate the effectiveness of the suggested scheme.

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Section: Problem Formulationmentioning

confidence: 99%

“…Using the controllers created in [33,35], the following laws can be applied to control the horizontal position:…”

Section: Horizontal and Vertical Control Designmentioning

confidence: 99%

Predefined-Time Fractional-Order Tracking Control for UAVs with Perturbation

Benaddy,

Labbadi,

Boubaker

et al. 2023

Mathematics

Self Cite

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“…Numerical solutions that can be computed with the Newton-Euler method are useful for implementing equipment that uses equations of motion, such as real-time feedback control of power assistance in human-machine coordination systems in the field of robotics [8,9]. However, when designing algorithms or conducting theoretical analysis of systems, the meaning of each physical term in the analytical solution obtained by the Lagrange method is extremely important.…”

Section: Introductionmentioning

confidence: 99%

Partial Lagrangian for Efficient Extension and Reconstruction of Multi-DoF Systems and Efficient Analysis Using Automatic Differentiation

Kusaka¹,

Tanaka

2022

Robotics

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In the fields of control engineering and robotics, either the Lagrange or Newton–Euler method is generally used to analyze and design systems using equations of motion. Although the Lagrange method can obtain analytical solutions, it is difficult to handle in multi-degree-of-freedom systems because the computational complexity increases explosively as the number of degrees of freedom increases. Conversely, the Newton–Euler method requires less computation even for multi-degree-of-freedom systems, but it cannot obtain an analytical solution. Therefore, we propose a partial Lagrange method that can handle the Lagrange equation efficiently even for multi-degree-of-freedom systems by using a divide-and-conquer approach. The proposed method can easily handle system extensions and system reconstructions, such as changes to intermediate links, for multi-degree-of-freedom serial link manipulators. In addition, the proposed method facilitates the derivation of the equations of motion-by-hand calculations, and when combined with an analysis algorithm using automatic differentiation, it can easily realize motion analysis and control the simulation of multi-degree-of-freedom models. Using multiple pendulums as examples, we confirm the effectiveness of system expansion and system reconstruction with the partial Lagrangians. The derivation of their equations of motion and the results of motion analysis by simulation and motion control experiments are presented. The system extensions and reconstructions proposed herein can be used simultaneously with conventional analytical methods, allowing manual derivations of equations of motion and numerical computer simulations to be performed more efficiently.

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