Output Feedback Sliding Mode Control of Quadcopter Using IMU Navigation

Nemati, Hamidreza; Montazeri, Allahyar

doi:10.1109/icmech.2019.8722899

Cited by 9 publications

(5 citation statements)

References 26 publications

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“…In other words, all the unknown information is lumped into the last state equation [4], [5]. This control strategy has several applications, for example, in electric motors [6], diesel machines [7], jet engines [8], robotics [9], quadcopters [10], ship positioning [11], control of air vehicles [12] and attitude control of spacecrafts [13].…”

Section: A Literature Reviewmentioning

confidence: 99%

Adaptive Backstepping Control Based on Global HOSM Differentiators With Dynamic Gains

Moreira,

Oliveira,

Iuri Pinheiro de Melo Queiroz

2024

IEEE Access

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The present paper proposes the application of global and exact differentiators with dynamic gains based on of higher-order sliding modes (HOSM) to the design of adaptive backstepping control for nonlinear uncertain systems of strict-feedback type. The use of this kind of differentiator in the closedloop system allows us to guarantee global uniform stability (for any initial conditions) due to the variable nature of the dynamic gain. The dynamic gain can grow or decrease with the unmeasured state. In addition, asymptotic output tracking is also assured. In order to illustrate the results of the new theorem, the proposed controller is applied to a high-performance aircraft system, suppressing the wing-rock phenomenon usually observed for fast-speed flight conditions. Comparison results with a linear-inexact differentiator, a local HOSM differentiator with fixed gains and the proposed global and exact HOSM differentiator with dynamic gain show the superiority of the latter over the former approaches. To demonstrate the practical efficacy of the proposed approach, we conclude with an experimental test featuring a DC motor and the novel differentiator-based backstepping control scheme.INDEX TERMS Adaptive systems, backstepping control, global sliding mode differentiator, uncertain nonlinear systems.

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Section: A Literature Reviewmentioning

confidence: 99%

Adaptive Backstepping Control Based on Global HOSM Differentiators With Dynamic Gains

Moreira,

Oliveira,

Iuri Pinheiro de Melo Queiroz

2024

IEEE Access

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“…In an idealized case, all parameters would be known and all states measured, allowing fullfeedback linearization control design methods to be used [6,7]. In many real applications, however, all states cannot be directly measured and parameters are not always fully defined to apply these strategies, hence output-only feedback approaches are often used [8].…”

Section: Introduction 1literature Reviewmentioning

confidence: 99%

Adaptive Control of Unmanned Aerial Vehicles with Varying Payload and Full Parametric Uncertainties

Imran,

Wood,

Montazeri

2024

Electronics

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This article investigates an adaptive tracking control problem for a six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV) with a variable payload mass. The changing payload introduces time-varying parametric uncertainties into the dynamical model, rendering a static control strategy no longer effective. To handle this issue, two adaptive schemes are developed to maintain the uncertainties in the translational and rotational dynamics. Initially, a virtual proportional derivative (PD) is designed to stabilize the horizontal position; however, due to an unknown and time-varying mass, an adaptive controller is proposed to generate the total thrust of the UAV. Furthermore, an adaptive controller is designed for the rotational dynamics, to handle parametric uncertainties, such as inertia and external disturbance parameters. In both schemes, a standard adaptive scheme using the certainty equivalence principle is extended and designed. A stability analysis was conducted with rigorous analytical proofs to show the performance of our proposed controllers, and simulations were implemented to assess the performance against other existing methods. Tracking fitness and total control efforts were calculated and compared with closed-loop adaptive tracking control (CLATC) and adaptive sliding mode control (ASMC). The results indicated that the proposed design better maintained UAV stability.

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“…There are an increasing number of research studies devoted to attitude estimation ( Moutinho et al., 2015 ; Nokhodberiz et al., 2019 ; Liang, 2017) . The commonly used stochastic approaches are the Kalman filter (KF) and extended Kalman filter (EKF) ( Nemati and Montazeri, 2019) . However, in KF-based methods (KF, EKF, and UKF), only Gaussian noise processes are considered and EKF suffers from the linearization issue.…”

Section: Introductionmentioning

confidence: 99%

Vision-based particle filtering for quad-copter attitude estimation using multirate delayed measurements

Sadeghzadeh-Nokhodberiz

Iranshahi

Montazeri

2023

Front. Robot. AI

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In this paper, the problem of attitude estimation of a quad-copter system equipped with a multi-rate camera and gyroscope sensors is addressed through extension of a sampling importance re-sampling (SIR) particle filter (PF). Attitude measurement sensors, such as cameras, usually suffer from a slow sampling rate and processing time delay compared to inertial sensors, such as gyroscopes. A discretized attitude kinematics in Euler angles is employed where the gyroscope noisy measurements are considered the model input, leading to a stochastic uncertain system model. Then, a multi-rate delayed PF is proposed so that when no camera measurement is available, the sampling part is performed only. In this case, the delayed camera measurements are used for weight computation and re-sampling. Finally, the efficiency of the proposed method is demonstrated through both numerical simulation and experimental work on the DJI Tello quad-copter system. The images captured by the camera are processed using the ORB feature extraction method and the homography method in Python-OpenCV, which is used to calculate the rotation matrix from the Tello’s image frames.

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Output Feedback Sliding Mode Control of Quadcopter Using IMU Navigation

Cited by 9 publications

References 26 publications

Adaptive Backstepping Control Based on Global HOSM Differentiators With Dynamic Gains

Adaptive Backstepping Control Based on Global HOSM Differentiators With Dynamic Gains

Adaptive Control of Unmanned Aerial Vehicles with Varying Payload and Full Parametric Uncertainties

Vision-based particle filtering for quad-copter attitude estimation using multirate delayed measurements

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