Acceleration Feedback Enhanced $H_{\infty}$ Control of Unmanned Aerial Vehicle for Wind Disturbance Rejection

2018 ◽  
Author(s):  
Bo Dai ◽  
Yuqing He ◽  
Guangyu Zhang ◽  
Weiliang Xu ◽  
Danwei Wang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Disturbance Rejection ◽  
Wind Disturbance ◽  
Acceleration Feedback ◽  
Aerial Vehicle

scholarly journals An overview of various kinds of wind effects on unmanned aerial vehicle

2019 ◽  
Vol 52 (7-8) ◽  
pp. 731-739 ◽  
Author(s):  
Bo Hang Wang ◽  
Dao Bo Wang ◽  
Zain Anwar Ali ◽  
Bai Ting Ting ◽  
Hao Wang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Great Influence ◽  
Wind Disturbance ◽  
Wind Fields ◽  
Wind Model ◽  
Aerial Vehicle ◽  
Low Altitude ◽  
The Stability ◽  
The Mathematical Model ◽  
Vehicle Movement

Attitude, speed, and position of unmanned aerial vehicles are susceptible to wind disturbance. The types, characteristics, and mathematical models of the wind, which have great influence on unmanned aerial vehicle in the low-altitude environment, are summarized, including the constant wind, turbulent flow, many kinds of wind shear, and the propeller vortex. Combined with the mathematical model of the unmanned aerial vehicle, the mechanism of unmanned aerial vehicle movement in the wind field is illustrated from three different kinds of viewpoints including velocity viewpoint, force viewpoint, and energy viewpoint. Some simulation tests have been implemented to show the effects of different kinds of wind on unmanned aerial vehicle’s path and flight states. Finally, some proposals are presented to tell reader in which condition, which wind model should be added to simulation, and how to enhance the stability of unmanned aerial vehicle for different kinds of wind fields.

Trajectory tracking control for a quadrotor unmanned aerial vehicle based on dynamic surface active disturbance rejection control

2020 ◽  
Vol 42 (12) ◽  
pp. 2198-2205
Author(s):  
Yong Zhang ◽  
Zengqiang Chen ◽  
Mingwei Sun
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Strategy ◽  
Disturbance Rejection ◽  
Active Disturbance Rejection Control ◽  
Dynamic Surface ◽  
Virtual Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Aerial Vehicle ◽  
Surface Active

This paper proposes a dynamic surface active disturbance rejection control (ADRC) strategy to deal with trajectory tracking problems for a quadrotor unmanned aerial vehicle (UAV). Compared with backstepping control, the design process of the dynamic controller is more simple; the dynamic surface control introduces a first-order filter to obtain the derivative of the virtual control, the purpose is to avoid the virtual control derivation, and to simplify the control law of the whole system. The ADRC technique is mainly used to reject the disturbances and stabilize the quadrotor UAV system. Parametric uncertainties and external disturbances have been considered for the whole system, the control strategy that proposed in this paper has been simulated by MATLAB and the advantages and effectiveness of the control strategy that proposed in the paper are shown by comparing with the classical ADRC.

Three-Dimensional Obstacle Avoidance of Blimp-Type Unmanned Aerial Vehicle Flying in Unknown and Non-Uniform Wind Disturbance

2007 ◽  
Vol 19 (2) ◽  
pp. 166-173 ◽  
Author(s):  
Hiroshi Kawano ◽  
Keyword(s):  
Motion Planning ◽  
Obstacle Avoidance ◽  
Unmanned Aerial Vehicle ◽  
High Performance ◽  
Three Dimensional ◽  
Longitudinal Motion ◽  
Wind Disturbance ◽  
Flow Disturbances ◽  
Markov Decision ◽  
Aerial Vehicle

A blimp-type unmanned aerial vehicle (BUAV) maintains its longitudinal motion using buoyancy provided by the air around it. This means the density of a BUAV equals that of the surrounding air. Because of this, the motion of a BUAV is seriously affected by flow disturbances, whose distribution is usually non-uniform and unknown. In addition, the inertia in the heading motion is very large. There is also a strict limitation on the weight of equipment in a BUAV, so most BUAVs are so-called under-actuated robots. From this situation, it can be said that the motion planning of the BUAV considering the stochastic property of the disturbance is needed for obstacle avoidance. In this paper, we propose an approach to the motion planning of a BUAV via the application of Markov decision process (MDP). The proposed approach consists of a method to prepare a discrete MDP model of the BUAV motion and a method to maintain the effect of the unknown wind on the BUAV’s motion. A dynamical simulation of a BUAV in an environment with wind disturbance shows high performance of the proposed method.

scholarly journals A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4504 ◽  
Author(s):  
Jia-Ying Wang ◽  
Bing Luo ◽  
Ming Zeng ◽  
Qing-Hao Meng
Keyword(s):  
Environmental Monitoring ◽  
Drag Coefficient ◽  
Wind Velocity ◽  
Unmanned Aerial Vehicle ◽  
Estimation Method ◽  
Velocity Estimation ◽  
Extended State Observer ◽  
Wind Disturbance ◽  
Extended State ◽  
Aerial Vehicle

Wind velocity (strength and direction) is an important parameter for unmanned aerial vehicle (UAV)-based environmental monitoring tasks. A novel wind velocity estimation method is proposed for rotorcrafts. Based on an extended state observer, this method derives the wind disturbance from rotors’ speeds and rotorcraft’s acceleration and position. Then the wind disturbance is scaled to calculate the airspeed vector, which is substituted into a wind triangle to obtain the wind velocity. Easy-to-implement methods for calculating the rotorcraft’s thrust and drag coefficient are also proposed, which are important parameters to obtain the wind drag and the airspeed, respectively. Simulations and experiments using a quadrotor in both hovering and flight conditions have validated the proposed method.

Altitude and attitude active disturbance rejection controller design of a quadrotor unmanned aerial vehicle

2016 ◽  
Vol 231 (9) ◽  
pp. 1732-1745 ◽  
Author(s):  
Jingxin Dou ◽  
Xiangxi Kong ◽  
Bangchun Wen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Disturbance Rejection ◽  
Dynamic Surface Control ◽  
State Observer ◽  
Extended State Observer ◽  
Extended State ◽  
Dynamic Surface ◽  
Active Disturbance Rejection ◽  
Surface Control ◽  
Aerial Vehicle

This paper presents a new active disturbance rejection controller to solve the altitude and attitude control problem for a quadrotor unmanned aerial vehicle. The proposed method requires only the output information of the system. Using the pitch subsystem as an example, the proposed controller is designed by using dynamic surface control strategy incorporated with tracking differentiator, and extended state observer, which is used to estimate the uncertain disturbance. The estimate states of extended state observer are used to design the dynamic surface control law for altitude and attitude tracking problem of the quadrotor unmanned aerial vehicle. The stability analysis proves that a sufficient condition of the asymptotic stability of the extended state observer is achieved, the asymptotic stability of the closed-loop system can be guaranteed, and the tracking feedback error can made arbitrarily small by adjusting the controller parameters. Several simulation results are presented to corroborate that the proposed control method has better effectiveness and robustness.

scholarly journals Anti-Disturbance Compensator Design for Unmanned Aerial Vehicle

2019 ◽  
Vol 26 (1) ◽  
pp. 86-103 ◽  
Author(s):  
Ibraheem Kasim Ibraheem
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Disturbance Rejection ◽  
Pid Controllers ◽  
Hurwitz Stability ◽  
Output Performance ◽  
Disturbance Rejection Control ◽  
Compensator Design ◽  
Control Scheme ◽  
Aerial Vehicle ◽  
Quadrotor System

In this paper, an Anti-Disturbance Compensator is suggested for the stabilization of a 6-DoF quadrotor Unmanned Aerial vehicle (UAV) system, namely, the Improved Active Disturbance Rejection Control (IADRC). The proposed Control Scheme rejects the disturbances subjected to this system and eliminates the effect of the uncertainties that the quadrotor system exhibits. The complete nonlinear mathematical model of the 6-DoF quadrotor UAV system has been used to design the four ADRCs units for the attitude and altitude stabilization. Stability analysis has been demonstrated for the Linear Extended State Observer (LESO) of each IADRC unit and the overall closed-loop system using Hurwitz stability criterion. A minimization to a proposed multi-objective Output Performance Index (OPI) is achieved in the MATLAB environment to tune the IADRCs parameters using Genetic Algorithm (GA). The IADRC has been tested for the 6-DOF quadrotor under different tracking scenarios, including disturbance rejection and uncertainties elimination and compared with nonlinear and linear PID controllers. The simulations showed the excellent performance of the proposed compensator against the controllers used in the comparison.

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