Autonomous Unmanned Aerial Vehicle System for Controlling Pest Bird Population in Vineyards

2012 ◽  
Author(s):  
Brian A. Grimm ◽  
Brooke A. Lahneman ◽  
Peter B. Cathcart ◽  
Robert C. Elgin ◽  
Greg L. Meshnik ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Method ◽  
Guidance System ◽  
Crop Loss ◽  
Control Methods ◽  
Willamette Valley ◽  
Bird Population ◽  
Management Culture ◽  
Control Techniques ◽  
Aerial Vehicle

Pest birds have long been a significant source of crop loss for grape growers, especially during the critical weeks leading up to harvest when grape sugar levels are high. In Oregon’s Willamette Valley, vineyards have seen a marked increase in crop loss in the last few years despite widespread use of intrusive gas cannons/shotguns and expensive netting systems. In order to deter this pest bird population, we have created an Unmanned Aerial Vehicle (UAV) package capable of autonomous flight, which incorporates common pest bird scare tactics into this dynamic platform. The system has been designed to launch, complete its mission waypoints, and land completely under autonomous control. By using this autonomous guidance system, we are able to employ visual, auditory, and predator mimicry pest bird control techniques in such a way as to discourage habituation. While radio controlled UAVs have been used for bird control in airport settings for many years, these systems require a trained operator to constantly guide the aircraft. The autonomous UAV system was designed for operation by an existing vineyard employee with minimal training. To capture widely accepted pest bird control techniques and management culture of Willamette Valley vineyards and gain information for design, implementation, and industry acceptance of this UAV project, we surveyed the owners of 225 local vineyards. Survey results indicated that vineyard owners are open to implementing innovative pest bird control methods that do not affect the terroir of their vineyards and that could replace the use of netting, which they do not view favorably despite its being the most effective pest bird control method to date. Results also indicated that pest birds are most damaging to a vineyard’s perimeter and that many vineyards employ someone to patrol this perimeter with a shotgun loaded with cracker shells. The UAV system is able to traverse the airspace above this perimeter without interfering with neighboring homes or beneficial predators in the area. By using proven pest bird control methods in an autonomous UAV system, we designed a device that brings an innovative solution to vineyard owners.

scholarly journals Aerial physical interaction via IDA-PBC

2019 ◽  
Vol 38 (4) ◽  
pp. 403-421 ◽  
Author(s):  
Burak Yüksel ◽  
Cristian Secchi ◽  
Heinrich H. Bülthoff ◽  
Antonio Franchi
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Method ◽  
Low Cost ◽  
Surface Inspection ◽  
Physical Interaction ◽  
External Disturbances ◽  
Aerial Vehicle ◽  
Passivity Based Control ◽  
The Stability ◽  
First Time

This paper proposes the use of a novel control method based on interconnection and damping assignment–passivity-based control (IDA-PBC) in order to address the aerial physical interaction (APhI) problem for a quadrotor unmanned aerial vehicle (UAV). The apparent physical properties of the quadrotor are reshaped in order to achieve better APhI performances, while ensuring the stability of the interaction through passivity preservation. The robustness of the IDA-PBC method with respect to sensor noise is also analyzed. The direct measurement of the external wrench, needed to implement the control method, is compared with the use of a nonlinear Lyapunov-based wrench observer and advantages/disadvantages of both methods are discussed. The validity and practicability of the proposed APhI method is evaluated through experiments, where for the first time in the literature, a lightweight all-in-one low-cost force/torque (F/T) sensor is used onboard of a quadrotor. Two main scenarios are shown: a quadrotor responding to external disturbances while hovering (physical human–quadrotor interaction), and the same quadrotor sliding with a rigid tool along an uneven ceiling surface (inspection/painting-like task).

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.

Model predictive control of an unmanned aerial vehicle

2017 ◽  
Vol 89 (2) ◽  
pp. 193-202 ◽  
Author(s):  
Halit Firat Erdogan ◽  
Ayhan Kural ◽  
Can Ozsoy
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Predictive Control ◽  
Control Method ◽  
Relevant Literature ◽  
Control Effort ◽  
Content Type ◽  
Multiple Input ◽  
Predictive Controller ◽  
Aerial Vehicle ◽  
Mimo Model

Purpose The purpose of this paper is to design a controller for the unmanned aerial vehicle (UAV). Design/methodology/approach In this study, the constrained multivariable multiple-input and multiple-output (MIMO) model predictive controller (MPC) has been designed to control all outputs by manipulating inputs. The aim of the autopilot of UAV is to keep the UAV around trim condition and to track airspeed commands. Findings The purpose of using this control method is to decrease the control effort under the certain constraints and deal with interactions between each output and input while tracking airspeed commands. Originality/value By using constraint, multivariable (four inputs and seven outputs) MPC unlike the relevant literature in this field, the UAV tracked airspeed commands with minimum control effort dealing with interactions between each input and output under disturbances such as wind.

scholarly journals Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach

2021 ◽  
Author(s):  
Ching-Wei Chang ◽  
Li-Yu Lo ◽  
Hiu Ching Cheung ◽  
Yurong Feng ◽  
An-Shik Yang ◽  
...  
Keyword(s):  
Trajectory Optimization ◽  
Control Method ◽  
Guidance System ◽  
Autonomous Landing ◽  
Ground Vehicle ◽  
Ground Station ◽  
Aerial Vehicle ◽  
Promising Solution ◽  
Marine Vessels ◽  
Long Endurance

This work aims to develop an autonomous system for the unmanned aerial vehicle (UAV) to land on a moving platform such as the automobile or marine vessels, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Different from most state-of-the-art UAV landing frameworks which rely on UAV’s onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such novel configuration can therefore lighten the burden of the UAV and computation power on the ground vehicle/marine vessel could be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted and the result shows that a precise autonomous landing on a 43 X 43 cm platform could be performed.

Tracking control of multiple unmanned aerial vehicles incorporating disturbance observer and model predictive approach

2019 ◽  
Vol 42 (5) ◽  
pp. 951-964 ◽  
Author(s):  
Boyang Zhang ◽  
Xiuxia Sun ◽  
Shuguang Liu ◽  
Xiongfeng Deng
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicle ◽  
Predictive Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Differential Evolution Algorithm ◽  
Reference Trajectory ◽  
Control Approach ◽  
Unknown Disturbances ◽  
Aerial Vehicle

This paper studies the disturbance observer-based model predictive control approach to deal with the unmanned aerial vehicle formation flight with unknown disturbances. The distributed control problem for a class of multiple unmanned aerial vehicle systems with reference trajectory tracking and disturbance rejection is formulated. Firstly, a local distributed controller is designed by using the model predictive control method to achieve stable tracking, where the local optimization problem is solved by an adaptive differential evolution algorithm. Then, a feedforward compensation controller is introduced by using a disturbance observer to estimate and compensate disturbances, and improve the ability of anti-interference. Besides, the stability of the proposed composite controller is analyzed as well. Finally, the simulation examples are provided to illustrate the validity of proposed control structure.

INTEGRATED PID CONTROLLER DESIGN FOR AN UNMANNED AERIAL VEHICLE WITH STATIC STABILITY

2013 ◽  
Vol 54 (3) ◽  
pp. 200-215 ◽  
Author(s):  
R. LI ◽  
Y. J. SHI ◽  
H. L. XU
Keyword(s):  
Fuzzy Control ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Control Method ◽  
Controller Design ◽  
Design Method ◽  
Design Procedure ◽  
Static Stability ◽  
Aerial Vehicle ◽  
Rolling Mode

AbstractThis paper presents an integrated guidance and control (IGC) design method for an unmanned aerial vehicle with static stability which is described by a nonlinear six-degree-of-freedom (6-DOF) model. The model is linearized by using small disturbance linearization. The dynamic characteristics of pitching mode, rolling mode and Dutch rolling mode are obtained by analysing the linearized model. Furthermore, an IGC design procedure is also proposed in conjunction with a proportional–integral–derivative (PID) control method and fuzzy control method. A PID controller is applied in the control loop of the elevator and aileron, and the attitude angle and attitude angular velocity are used as compensation feedback, giving a simple and low-order control law. A fuzzy control method is applied to perform the cross-coupling control of rolling and yawing. Finally, the 6-DOF simulation shows the effectiveness of the developed method.

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