Robust control for attitude tracking problem for a quadrotor unmanned aerial vehicle

2013 ◽  
Author(s):  
M Rida Mokhtari ◽  
Brahim Cherki
Keyword(s):  
Robust Control ◽  
Unmanned Aerial Vehicle ◽  
Tracking Problem ◽  
Attitude Tracking ◽  
Aerial Vehicle

Output feedback observer-based dynamic surface controller for quadrotor UAV using quaternion representation

2016 ◽  
Vol 231 (14) ◽  
pp. 2537-2548 ◽  
Author(s):  
Jingxin Dou ◽  
Xiangxi Kong ◽  
Xiaozhe Chen ◽  
Bangchun Wen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Output Feedback ◽  
Dynamic Surface Control ◽  
Control Technique ◽  
Dynamic Surface ◽  
Attitude Tracking ◽  
Uncertain Disturbances ◽  
Aerial Vehicle ◽  
System Output ◽  
Quaternion Representation

An output feedback observer-based dynamic surface controller is presented for attitude tracking problem of the quadrotor unmanned aerial vehicle, which is subject to measurement noise and external disturbances. The dynamics model of the quadrotor unmanned aerial vehicle is firstly introduced with the quaternion representation. Subsequently, a nonlinear augmented observer is introduced for simultaneously estimating the unavailable states and uncertain disturbances from the measurement of system output. The output feedback controller based on the nonlinear augmented observer is designed with the dynamic surface control technique. The Lyapunov stability analysis shows that the attitude tracking performance is ensured and all signals of the closed-loop system remain bounded. Finally, simulative and experimental results are carried out to illustrate, compared with other observer-based controller, the effectiveness of the proposed method is better.

Tracking Control Design for Quadrotor Unmanned Aerial Vehicle

2017 ◽  
Vol 67 (3) ◽  
pp. 245 ◽  
Author(s):  
Sudhir Nadda ◽  
A. Swarup
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Strategy ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Backstepping Control ◽  
Control Technique ◽  
Quadrotor Uav ◽  
Attitude Tracking ◽  
Aerial Vehicle

The model of a quadrotor unmanned aerial vehicle (UAV) is nonlinear and dynamically unstable. A flight controller design is proposed on the basis of Lyapunov stability theory which guarantees that all the states remain and reach on the sliding surfaces. The control strategy uses sliding mode with a backstepping control to perform the position and attitude tracking control. This proposed controller is simple and effectively enhance the performance of quadrotor UAV. In order to demonstrate the robustness of the proposed control method, White Gaussian Noise and aerodynamic moment disturbances are taken into account. The performance of the nonlinear control method is evaluated by comparing the performance with developed linear quadratic regulator and existing backstepping control technique and proportional-integral-derivative from the literature. The comparative performance results demonstrate the superiority and effectiveness of the proposed control strategy for the quadrotor UAV.

L1 neural network adaptive fault-tolerant controller for unmanned aerial vehicle attitude control system

2021 ◽  
pp. 095441002098409
Author(s):  
Yan Zhou ◽  
Huiying Liu ◽  
Huijuan Guo ◽  
Jing Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Attitude Control System ◽  
Attitude Tracking ◽  
Nonlinear Uncertainties ◽  
Aerial Vehicle

In this article, a L1 neural network adaptive fault-tolerant controller is exploited for an unmanned aerial vehicle attitude control system in presence of nonlinear uncertainties, such as system uncertainties, external disturbances, and actuator faults. A nonlinear dynamic inversion controller with sliding mode control law is designed as the outer-loop controller to track the attitude angles quickly and accurately which reduces dependence on model accuracy. A L1 neural network adaptive controller of the inner loop is introduced to compensate the nonlinear uncertainties and have a good attitude tracking. The radial basis function neural network technique is introduced to approximate a lumped nonlinear uncertainty and guarantee the stability and transient performance of the closed-loop system, instead of converting it to a half-time linear system by the parametric linearization method. Simulation results demonstrate the effectiveness of the proposed controller.

scholarly journals РОБАСТНОЕ УПРАВЛЕНИЕ БЕСПИЛОТНЫМ ЛЕТАТЕЛЬНЫМ АППАРАТОМ ПРИ НЕОПРЕДЕЛЕННЫХ СКОРОСТЯХ

2018 ◽  
pp. 4-12
Author(s):  
Будиба Уиссам
Keyword(s):  
Control System ◽  
Robust Control ◽  
Nonlinear Control ◽  
Unmanned Aerial Vehicle ◽  
Quality Criteria ◽  
Nominal Model ◽  
Ansys Cfx ◽  
Aerial Vehicle ◽  
Aerodynamic Parameters ◽  
Aerodynamic Lift

This paper presents the method for implementing robust control using a nominal model of an unmanned aerial vehicle (UAV). The operation of a classical controller in a nonlinear control system in the event of disturbing influences does not satisfy the specified quality criteria. This changes the aerodynamic parameters, and the system becomes unstable. To eliminate unwanted deviations in the control system of the aircraft introduced robust control. The introduction of such a correction control signal allows you to fend off all sorts of failures and disturbances that lead to uncontrolled control. Changes in the aerodynamic lift coefficients, coefficient of resistance, and moments affect the model of the object. The nominal model is calculated by calculating the coefficients with the ANSYS-CFX software and the calculation is confirmed experimentally. Errors are also modeled by this software, and the ranges of variation of each coefficient are a set of failures.

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