Fuzzy-Lyapunov based quadrotor controller design

Varga, Maja; Bogdan, Stjepan

doi:10.23919/ecc.2009.7074523

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…They showed that the PID controller cannot be used as an effective technique for tracking problems. Varga and Bogdan (2009) showed that a fuzzy Lyapunov-based controller can be used as an effective technique for tracking tasks with a predefined trajectory. Wai (2007) presented an adaptive fuzzy sliding-mode controller.…”

Section: Related Workmentioning

confidence: 99%

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

Vial

Dong

Alshbatat

2016

IJISTA

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It is challenging to stabilise an unmanned quad-rotor aerial vehicle when a dynamic change in its model parameters or failure of its actuator occurs. In this paper, a quad-rotor unmanned aerial vehicle (UAV) is controlled based on model reference adaptive control (MRAC) and a linear quadratic regulator (LQR). The kinematics and dynamics of the quad-rotor are calculated, and Lyapunov's direct stability method is used to design the MRAC. In order to evaluate the performance of the adaptive control algorithms in the presence of thrust loss that may occur due to component failure or physical damage, a real quad-rotor is built from scratch using commercial components. Both controllers are designed, implemented and tested using AVR microcontrollers. Comparison is made between the controllers under normal and faulty situations and the effectiveness of the proposed control strategy is verified. Simulation and experimental results show that both controllers have satisfactory performance under normal conditions and even in the presence of the partial loss of thrust that may occur due to the loss of control effectiveness in one of the rotors or the damage of one propeller, superior system performance is observed using the proposed MRAC controller.

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Section: Related Workmentioning

confidence: 99%

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

Vial

Dong

Alshbatat

2016

IJISTA

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“…The research presented in [6] shows how PID controllers cannot be used as effective set point tracking controller. Fuzzy based controller is presented in [7]. This controller exhibits good tracking results for simple, predefined trajectories.…”

Section: Introductionmentioning

confidence: 99%

Hybrid fly-by-wire quadrotor controller

Orsag

Poropat

Bogdan

2010

2010 IEEE International Symposium on Industrial Electronics

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UDK Original scientific paper This article presents one solution to a quadrotor control problem that is based on a discrete automaton. This automaton combines classical PID and more sophisticated LQ controllers to create a hybrid control system. This closed loop control concept is expanded with an open loop controller that enables the aircraft to perform aggressive flying maneuvers. The combination of open and closed loop controllers builds a hybrid controller concept that allows directed and autonomous flying of the quadrotor aerial vehicle. Proposed control concept was tested on an elaborate mathematical model. The article discusses these test results and presents the means to develop such a controller. Key words: Hybrid control, Rotorcraft, Unmanned aerial vehicleHibridni sustav daljinskog upravljanja lebdjelicom. U radu je opisan hibridni upravljački koncept bespilotne letjelice pogonjene sčetiri rotora, koji objedinjuje klasične PID regulatore i naprednije LQ regulatore primjenom Mooreova automata. Takav je hibridni koncept upravljanja u zatvorenoj petlji nadograen upravljanjem u otvorenoj petlji koje omogućuje ostvarenje agresivnih letačkih manevara. Osim toga, kombinacija upravljanja u otvorenoj i zatvorenoj petlji omogućuje i daljinsko upravljanje letjelicom zasnovano na vizualnoj povratnoj vezi. Predloženi sustav upravljanja letjelicom testiran je na iscrpnom matematičkom modelu letjelice.Ključne riječi: bespilotna letjelica, hibridno upravljanje, rotokopter

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“…In addition, Varga & Bogdan [9] have applied fuzzy-Lyapunov to control the positions of x, y, and z in quadrotor. There are six fuzzy controls used to control the quadrotor namely x-axis, y-axis, z-axis and yaw fuzzy controls.…”

Section: Hovering Control Of Quadrotor Based On Fuzzy Logic (Nia Mahamentioning

confidence: 99%

“…Moment of pitch force (8) 4. Moment of yaw force (9) The translational dynamics of the quadrotor comparable to the influence of the Coriolis force is determined based on the second law of Newton [12] that is as follows: which m = quadrotor mass (kg), a = acceleration (m/s 2 )and F is the force generated by quadrotor where…”

Section: Quadrotor 21 Quadrotor Modelingmentioning

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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Fuzzy-Lyapunov based quadrotor controller design

Cited by 9 publications

References 5 publications

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

Hybrid fly-by-wire quadrotor controller

Hovering Control of Quadrotor Based on Fuzzy Logic

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