Application of L1 Adaptive Control Augmentation to the Flying Wing Unmanned Aerial Vehicle

2011 ◽  
Author(s):  
Li Gao ◽  
Wenhai Wu ◽  
Siyu Zhou
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicle ◽  
L1 Adaptive Control ◽  
Aerial Vehicle

scholarly journals Geometric L1 Adaptive Attitude Control for a Quadrotor Unmanned Aerial Vehicle

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Prasanth Kotaru ◽  
Ryan Edmonson ◽  
Koushil Sreenath
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Reference Model ◽  
Adaptive Controller ◽  
Control Approach ◽  
L1 Adaptive Control ◽  
Attitude Tracking ◽  
Aerial Vehicle ◽  
L1 Adaptive Controller

Abstract In this paper, we study the quadrotor unmanned aerial vehicle (UAV) attitude control on special orthogonal group (SO(3)) in the presence of unknown disturbances and model uncertainties. L1 adaptive control for UAVs using Euler angles/quaternions is shown to exhibit robustness and precise attitude tracking in the presence of disturbances and uncertainties. However, it is well known that dynamical models and controllers that use Euler angle representations are prone to singularities and typically have smaller regions of attraction while quaternion representations are subject to the unwinding phenomenon. To avoid such complexities, we present a geometric L1 adaptation control law to estimate the uncertainties. A model reference adaptive control approach is implemented, with the attitude errors between the quadrotor model and the reference model defined on the manifold. Control laws for the quadrotor and reference models are developed directly on SO(3) to track the desired trajectory while rejecting the uncertainties. Control Lyapunov function-based analysis is used to show the exponential input-to-state stability of the attitude errors. The proposed L1 adaptive controller is validated using numerical simulations. Preliminary experimental results are shown comparing a geometric proportional-derivative controller to the geometric L1 adaptive controller. Experimental validation of the proposed controller is carried out on an Autel X-star quadrotor.

Adaptive control of an unmanned aerial vehicle

2017 ◽  
Author(s):  
V. F. Nguen ◽  
A. V. Putov ◽  
T. T. Nguen
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicle ◽  
Aerial Vehicle

scholarly journals Modeling and controlling of quadrotor aerial vehicle equipped with a gripper

2019 ◽  
Vol 52 (5-6) ◽  
pp. 577-587 ◽  
Author(s):  
Zain Anwar Ali ◽  
Xinde Li
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicle ◽  
Degrees Of Freedom ◽  
Control Structure ◽  
Arm Movement ◽  
Transient Behavior ◽  
Model Reference Adaptive Control ◽  
Model Reference ◽  
Aerial Vehicle ◽  
Model Reference Adaptive

Arm mounted unmanned aerial vehicles provide more feasible and attractive solution to manipulate objects in remote areas where access to arm mounted ground vehicles is not possible. In this research, an under-actuated quadrotor unmanned aerial vehicle model equipped with gripper is utilized to grab objects from inaccessible locations. A dual control structure is proposed for controlling and stabilization of the moving unmanned aerial vehicle along with the motions of the gripper. The control structure consists of model reference adaptive control augmented with an optimal baseline controller. Although model reference adaptive control deals with the uncertainties as well as attitude controlling of unmanned aerial vehicle, baseline controller is utilized to control the gripper, remove unwanted constant errors and disturbances during arm movement. The proposed control structure is applied in 6-degree-of-freedom nonlinear model of a quadrotor unmanned aerial vehicle equipped with gripper having (2 degrees of freedom) robotic limb; it is applicable for the simulations to desired path of unmanned aerial vehicle and to grasp object. Moreover, the efficiency of the presented control structure is compared with optimal baseline controller. It is observed that the proposed control algorithm has good transient behavior, better robustness in the presence of continuous uncertainties and gripper movement involved in the model of unmanned aerial vehicle.

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