Quadrotor modelling and control

Jithu, G; Jayasree, P R

doi:10.1109/iceeot.2016.7754868

Cited by 21 publications

(8 citation statements)

References 9 publications

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“…Modeling of a quad-rotor is based on the overall model which is built with the dynamic models of the quad-rotor in addition to the DC motor dynamics that must be taken into account. A basic model of an unmanned quad-rotor [17][18][19][20] is shown in Fig. 1.…”

Section: Dynamic Model Of the Quad-rotormentioning

confidence: 99%

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Neural networks on-line optimized PID controller with wind gust rejection for a quad-rotor

Jabeur¹,

Seddik

2022

IRASE

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In this paper a complete methodology of modeling and control of quad-rotor aircraft is exposed. In fact, a PD on-line optimized Neural Networks Approach (PD-NN) is developed and applied to control the attitude of a quad-rotor that is evolving in hostile environment with wind gust disturbances and should maintain its position despite of these troubles. Whereas PD classical controllers are dedicated for the positions, altitude and speed control. The main objective of this work is to develop a smart Self-Tuning PD controller for attitude angles control, based on neural networks capable of controlling the quad-rotor for an optimized performance thus following a desired trajectory. Many problems could arise if the quad-rotor is evolving in hostile environments presenting irregular troubles such as wind gusts modeled and applied to the overall system. The quad-rotor has to rapidly achieve tasks while guaranteeing stability and precision and must behave quickly with regards to decision making fronting turbulences. This technique offers some advantages over conventional control methods such as PD controllers. Simulation results are achieved with the use of Matlab/Simulink environment and are established on a comparative study between PD and PD-NN controllers founded on wind disturbances application. These obstacles are applied with numerous degrees of strength to test the quad-rotor comportment. Experimental results are reached with the use of the V-REP environment with which some trajectories are tracked and then applied on a BLADE Inductrix FPV+. These simulations and experimental results are acceptable and have confirmed the efficiency of the proposed PD-NN approach. In fact, this controller has fairly smaller errors than the PD controller and has an improved ability to reject troubles. Moreover, it has confirmed to be extremely vigorous and efficient fronting disturbances in the form of wind disturbances.

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Section: Dynamic Model Of the Quad-rotormentioning

confidence: 99%

“…If the lateral motors are used, the roll movement is achieved similarly. If the speed of the front and rear motors is increased (decreased) and the speed of the lateral motors is decreased (increased), the yaw movement is activated [18].…”

Section: Dynamic Model Of the Quad-rotormentioning

confidence: 99%

Neural networks on-line optimized PID controller with wind gust rejection for a quad-rotor

Jabeur¹,

Seddik

2022

IRASE

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“…As it is known, flight stability and performance are susceptible to degradation due to wind gusts [19,20,21]. Estimating such wind disturbances with sensors and using them to inform flight controls can recover safety.…”

Section: Introductionmentioning

confidence: 99%

Optimized Neural Networks-PID Controller with Wind Rejection Strategy for a Quad-Rotor

Jabeur¹,

Seddik²

2021

Journal of Robotics and Control

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In this paper a full approach of modeling and intelligent control of a four rotor unmanned air vehicle (UAV) known as quad-rotor aircraft is presented. In fact, a PID on-line optimized Neural Networks Approach (PID-NN) is developed to be applied to angular trajectories control of a quad-rotor. Whereas, PID classical controllers are dedicated for the positions, altitude and speed control. The goal of this work is to concept a smart Self-Tuning PID controller, for attitude angles control, based on neural networks able to supervise the quad-rotor for an optimized behavior while tracking a desired trajectory. Many challenges could arise if the quad-rotor is navigating in hostile environments presenting irregular disturbances in the form of wind modeled and applied to the overall system. The quad-rotor has to quickly perform tasks while ensuring stability and accuracy and must behave rapidly with regards to decision making facing disturbances. This technique oﬀers some advantages over conventional control methods such as PID controller. Simulation results are founded on a comparative study between PID and PID-NN controllers based on wind disturbances. These later are applied with several degrees of strength to test the quad-rotor behavior and stability. These simulation results are satisfactory and have demonstrated the effectiveness of the proposed PD-NN approach. In fact, the proposed controller has relatively smaller errors than the PD controller and has a better capability to reject disturbances. In addition, it has proven to be highly robust and efficient face to turbulences in the form of wind disturbances.

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“…A lot of research related to unmanned vehicles has been done, an example is in [1] which discusses modeling and control of autonomous quadrotor which is one type of unmanned aerial vehicle, the control method used in the study is the PID method. Position tracking research on unmanned air rides was also carried out on [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Autodrive Land Vehicle Control by Using PID

Swadexi

Rudi

Heriansyah

2019

JSAT

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In towards industry 4.0, the autodrive vehicle is needed to give people relaxed driving. There are many research in autodrive vehicle such as waymo-the Google driving car project and Tesla Self Driving Autopilot. In This paper is presented about Autodrive Land Vehicle (ALV) control by using PID. The autodrive Land vehicle can drive autonomously by using GPS Information such as Latitude and longitude to navigate in an area. The vehicle is controled to follow the given waypoint that set by operator on ground control station. PID control is used to control steering of the vehicle's front wheel and to control the heading of the vehicle. From the Implementation result, it is obtained that the vehicle could track the given waypoint with small error.

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Quadrotor modelling and control

Cited by 21 publications

References 9 publications

Neural networks on-line optimized PID controller with wind gust rejection for a quad-rotor

Neural networks on-line optimized PID controller with wind gust rejection for a quad-rotor

Optimized Neural Networks-PID Controller with Wind Rejection Strategy for a Quad-Rotor

Autodrive Land Vehicle Control by Using PID

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