scholarly journals Aspects Regarding Fly Control of Quadcopter

2016 ◽  
Vol 3 (1-2.) ◽  
Author(s):  
Endrowednes Kuantama ◽  
Ioan Tarca ◽  
Radu Tarca ◽  
Dan Craciun
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Attitude Determination ◽  
Comparative Data ◽  
Reference Line ◽  
Mathematical Formula ◽  
Control Factors ◽  
Aerial Vehicle ◽  
Orientation Sensor ◽  
The Stability ◽  
Fly Control

Quadcopter is one of Unmanned Aerial Vehicle (UAV) which has two pairs of identical fixed pitched rotor propellers. It can fly autonomously based on pre-programmed flight or manually controlled by a remote, and every movement achieved by varying the speed of each rotor independently. The orientation of quadcopter axes relative to a reference line and its direction of motion are known as attitude. Fly control factors are affected by attitude determination which can be calculated from 3 possible angles using combined measurement. Gyroscope and accelerometer are primary sensors to control quadcopter attitude, but magnetometer sensor and GPS also used to enhance the stability during flight. This paper will focus on details of function and mathematical formula of every factor regarding fly control and comparative data of 2 types of orientation sensor used in this system.

Dynamic gyroscope sensors fusion and calibration using Kalman filter

2018 ◽  
Vol 7 (2.3) ◽  
pp. 18
Author(s):  
Mishell D. Lawas ◽  
Sherwin A. Guirnaldo
Keyword(s):  
Kalman Filter ◽  
Unmanned Aerial Vehicle ◽  
Systems Design ◽  
Mean Square ◽  
Fusion Technique ◽  
System Experiment ◽  
Aerial Vehicle ◽  
Sensors Fusion ◽  
The Stability ◽  
Actual Test

The stability of an Unmanned Aerial Vehicle (UAV) during actual flight conditions is one parameter that is very important in systems design in Avionics. In this research, two sensors, the autopilot microcontroller and the smartphone gyroscope sensing mechanism, are fused together and calibrated to monitor the flying behavior of the UAV prior to actual test flights. The two fused sensors and installed inside the UAV for relatively increased sensing accuracy and best flight monitoring capabilities. A Kalman filter is used as fusion technique and a Stewart Motion tracker is also used to test the ruggedness and accuracy of the fused sensor system. Experiment results show that fused system can give an overall mean square error or 1.9729.

scholarly journals An overview of various kinds of wind effects on unmanned aerial vehicle

2019 ◽  
Vol 52 (7-8) ◽  
pp. 731-739 ◽  
Author(s):  
Bo Hang Wang ◽  
Dao Bo Wang ◽  
Zain Anwar Ali ◽  
Bai Ting Ting ◽  
Hao Wang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Great Influence ◽  
Wind Disturbance ◽  
Wind Fields ◽  
Wind Model ◽  
Aerial Vehicle ◽  
Low Altitude ◽  
The Stability ◽  
The Mathematical Model ◽  
Vehicle Movement

Attitude, speed, and position of unmanned aerial vehicles are susceptible to wind disturbance. The types, characteristics, and mathematical models of the wind, which have great influence on unmanned aerial vehicle in the low-altitude environment, are summarized, including the constant wind, turbulent flow, many kinds of wind shear, and the propeller vortex. Combined with the mathematical model of the unmanned aerial vehicle, the mechanism of unmanned aerial vehicle movement in the wind field is illustrated from three different kinds of viewpoints including velocity viewpoint, force viewpoint, and energy viewpoint. Some simulation tests have been implemented to show the effects of different kinds of wind on unmanned aerial vehicle’s path and flight states. Finally, some proposals are presented to tell reader in which condition, which wind model should be added to simulation, and how to enhance the stability of unmanned aerial vehicle for different kinds of wind fields.

scholarly journals Stepwise fusion algorithm with dual correction for multi-sensor navigation

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141877993 ◽  
Author(s):  
Rong Wang ◽  
Zhi Xiong ◽  
Jianye Liu ◽  
Yuxuan Cao
Keyword(s):  
High Altitude ◽  
Unmanned Aerial Vehicle ◽  
Error Estimation ◽  
Attitude Determination ◽  
Vehicle Navigation ◽  
Fusion Algorithm ◽  
Aerial Vehicle ◽  
Determination System ◽  
Long Endurance ◽  
Sensor Navigation

In high-altitude, long-endurance unmanned aerial vehicles, a celestial attitude determination system is used to enhance the inertial navigation system (INS)/global positioning system (GPS) to achieve the required attitude performance. The traditional federal filter is not applicable for INS/GPS/celestial attitude determination system information fusion because it does not consider the mutually coupled relationship between the horizontal reference error in the celestial attitude determination system and the navigation error; this limitation results in reduced navigation accuracy. This article proposes a novel stepwise fusion algorithm with dual correction for multi-sensor navigation. Considering the horizontal reference error, the celestial attitude determination system measurement model is constructed and the issues involved in applying the federal filter are discussed. Then, preliminary error estimation and horizontal reference compensation are added to the navigation architecture. In addition, a sequential update strategy is derived to estimate the attitude error with the compensated celestial attitude determination system based on the preliminary estimation. A stepwise correction filtering algorithm with interactive preliminary and sequential updates that can effectively fuse celestial attitude determination system measurements with the INS/GPS is constructed. High-altitude, long-endurance unmanned aerial vehicle navigation in a remote sensing task is simulated to verify the performance of the proposed method. The simulation results demonstrate that the horizontal reference error is effectively compensated, and the attitude accuracy is significantly improved after stepwise error estimation and correction. The proposed method also provides a novel multi-sensor integrated navigation architecture with mutually coupled errors; this architecture is beneficial in unmanned aerial vehicle navigation applications.

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).

scholarly journals Planar Smooth Path Guidance Law for a Small Unmanned Aerial Vehicle with Parameter Tuned by Fuzzy Logic

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yang Chen ◽  
Jianhong Liang ◽  
Chaolei Wang ◽  
Yicheng Zhang ◽  
Tianmiao Wang ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Unmanned Aerial Vehicle ◽  
Oscillation Amplitude ◽  
Mathematical Expression ◽  
Path Following ◽  
Simulation Experiments ◽  
Guidance Law ◽  
Smooth Path ◽  
Aerial Vehicle ◽  
The Stability

A guidance law has been designed to guide the small unmanned aerial vehicle towards the predefined horizontal smooth path. The guidance law only needs the mathematical expression for the predefined path, the positions, and the velocities of the vehicle in the horizontal inertial frame. The stability of the guidance law has been demonstrated by the Lyapunov stability arguments. In order to improve the path following performance, one of the parameters of the guidance law is tuned by using the fuzzy logic which will still keep its stability. The simulation experiments in the Matlab/Simulink environment to realize the square-, circular-, and the athletics track-style paths following are given to verify the effectiveness of the proposed method. The simulation results show that the path following performance will be improved with smaller overshoot and oscillation amplitude and shorter arrival time with the parameter tuned.

Mathematical Model for Studying the Evolution of Multi-Role Unmanned Aerial Vehicle in Turbulent Atmosphere

2013 ◽  
Vol 325-326 ◽  
pp. 984-989
Author(s):  
Cristina Mihailescu ◽  
Ioan Farcasan
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Degrees Of Freedom ◽  
Guidance System ◽  
Theoretical Development ◽  
Atmospheric Conditions ◽  
Aerial Vehicle ◽  
Six Dof ◽  
The Stability

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used for local observations, surveillance and monitoring of interest area or as a training target for anti-aircraft systems. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using a nonlinear model, as well as a linear one for obtaining the guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and an autonomous control system. This theoretical development allows us to build the stability matrix, command matrix and the control matrix and finally to analyze the stability of autonomous UAV flight. A robust guidance system, based on Kalman filter will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analyzed. The paper is inspired by national project SAMO (Autonomous Aerial Monitoring System for Interest Areas of Great Endurance). Keywords: UAV, Simulation, Control, Guidance, Endurance, Surveillance, Monitoring, Kalman filter

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