Altitude and horizontal motion control of quadrotor UAV in the presence of air turbulence

Joyo, M. Kamran; Hazry, D.; Ahmed, Syed Faiz; Tanveer, M. Hassan; Warsi, Faizan A.; Hussain, Abadal-Salam T.

doi:10.1109/spc.2013.6735095

Cited by 29 publications

(15 citation statements)

References 4 publications

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“…In reference [10], the UAV's robust response in the presence of uncertainties and disturbances was guaranteed to satisfy the path tracking performance. Moreover, the UAV needed to carry a robust controller that could respond quickly to reduce the risk of terrific descent and drift from its original position [11]. In reference [12], the robust controller yielded an excellent dynamic response, a smaller tracking error, and an excellent robustness against unknown certainties, such as the actual ground effect and atmospheric disturbances.…”

Section: Related Workmentioning

confidence: 99%

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Sheng

et al. 2021

IEEE Access

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The unmanned aerial vehicle (UAV) is inexpensive and offers a fast response speed and robust flexibility; thus, it is a promising tool in the maritime buoyage inspection scenario, which involves monitoring and accessing a lateral mark system far away from the coast. However, two main problems can occur during inspection. The first is extreme weather conditions, resulting in a deviation between the inspection route and the design route. The second is that the buoyage beacons are visited only once. Therefore, this article proposes a buoyage inspection system consisting of a single UAV and random coastal buoys. The UAV automatically takes off from the depot, performs a self-check on the buoy beacons, and then returns to the depot. A cascade active disturbance rejection controller (ADRC) is designed to adjust the real-time trajectory of the UAV system. A feasible trajectory planning method is also designed based on the continuous Hopfield neural network (CHNN) and genetic algorithm (GA) to minimize the inspection distance. Extensive simulations are conducted to demonstrate the effectiveness of the proposed method.

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Section: Related Workmentioning

confidence: 99%

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Sheng

et al. 2021

IEEE Access

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“…Altitude control is required to ensure that the quadrotor is at a secure altitude [15]- [18]. So that it is also responsible for restoring the quadrotor to a secure state at a certain altitude if it performs impaired position due to air turbulence.…”

Section: Altitude Controlmentioning

confidence: 99%

Hovering Control of Quadrotor Based on Fuzzy Logic

Raharja¹,

Firmansyah²,

Cahyadi³

et al. 2017

IJPEDS

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Quadrotor is one of rotary wing UAV types which is able to perform a hover position. In order to take off, landing, and hover, it needs controllers. Conventional controllers have been widely applied in quadrotor, yet they have drawbacks namely overshoot. This paper presents attitude and altitude control algorithm in order to obtain a response as quadrotor hovered optimally within minimum overshoot, rise time, and settling time. The algorithm used is Fuzzy Logic Controller (FLC) algorithm with Mamdani method. By using the algorithm, the quadrotor is able to hover with minimum overshoot and maximum rise time. The advantage of the algorithm is that it does not require linearization model of the quadrotor. Keyword:Altitude control Attitude control Fuzzy logic controller Mamdani Quadrotor Copyright © 2017 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Nia Maharani Raharja, Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia. Email: nia.sie13@mail.ugm.ac.id INTRODUCTIONQuadrotor is basically unstable because it is a non-linear model that has many variables with 6 degrees of freedom affected by four actuators. Previous researchers created quadrotor models in dynamics and kinematics represented in two models, namely nonlinear and linear. Quadrotor modeling needs some consideration, namely solid frames, rotor placement on each angle having symmetrical distance, and the position of the center of gravity (COG) is right at the midpoint of the crossing frame arm. Euler-Lagrange and Newton-Euler methods are generally used in aircraft modeling, however, Newton-Euler is more widely used because it is more easily understood.Researches on quadrotor have been widely conducted by previous researchers in the field of control by using conventional traditional controls as practiced by Bouabdallah et al [1] using the configuration Plus for microquadrotor OS4 model weighing 240 grams controlled by PID and LQR control methods by referring to six states of roll, pitch, and yaw based attitude. In designing PID control of non-linear model of quadrotor obtained from the dynamics and kinematics, it is firstly linearized to obtain a state variable in that the stability can be identified.Quadrotor modeling has been successfully developed by Bouabdallah & Siegwart [2] by modeling quadrotor from 6 to 12 states. In addition they modify backstepping algorithm by adding integral then called integral-backstepping. The algorithm is used to control the attitude and altitude, so that it can take off and landing autonomously. The algorithm is also used to control the position of the quadrotor in order to perform fly autonomously and avoid obstacles. With the algorithm, there is no overshoot when it hovers at the desired height but it takes a long raise time.One of the criteria for good performance in the control of hover is a quick or minimum response. However, the rapid response tends to cause oscillation and requires a fairly large control signaling. I...

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“…Most countries are using UAV technology for military or civil purposes. Advances in technology have made UAV become an important asset for handling special and important mission [1]. One of the UAV type is the Micro Aerial Vehicle (MAV).…”

Section: Internal Air Flow Analysis Of a Bladeless Micro Aerial Vehicmentioning

confidence: 99%

Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

Othman¹,

Zuradzman²,

Hazry³

et al. 2014

AIP Conference Proceedings

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Articles you may be interested inComputational fluid dynamics analysis of external recirculation flow at updraft gasifier using ejector AIP Conf. Proc. 1440, 936 (2012); 10.1063/1.4704307Design of air springs for improved frequency response characteristics using computational fluid dynamics Results of flow-field quantities from computational fluid dynamics (CFD) analysis of a flow-excited Helmholtz resonator Analysis of nuclear thermal propulsion systems using computational fluid dynamics AIP Conf.Abstract. This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors and the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.

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Altitude and horizontal motion control of quadrotor UAV in the presence of air turbulence

Cited by 29 publications

References 4 publications

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Hovering Control of Quadrotor Based on Fuzzy Logic

Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

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