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Trajectory Tracking and Payload Dropping of an Unmanned Quadrotor Helicopter Based on GS-PID and Backstepping Control

Title:

Trajectory Tracking and Payload Dropping of an Unmanned Quadrotor Helicopter Based on GS-PID and Backstepping Control

Qiao, Jing (2018) Trajectory Tracking and Payload Dropping of an Unmanned Quadrotor Helicopter Based on GS-PID and Backstepping Control. Masters thesis, Concordia University.

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Abstract

Two useful control techniques, the Gain-Scheduled Proportional-Integral-Derivative (GS-PID) control and backstepping control, have been applied by using quadrotor Unmanned Aerial Vehicle (UAV) in the applications of trajectory tracking and payload dropping operations in this thesis. These control algorithms are analyzed and verified through software simulations and experimental tests.
The dynamic model of the quadrotor UAV is firstly established using Newton-Euler laws. The quadrotor comes with a symmetric, nonlinear and multiple-input-multiple output (MIMO) dynamic model.
The GS-PID control algorithm is implemented firstly in take-off, trajectory tracking, payload dropping, and landing periods of flight in trajectory tracking and payload dropping scenarios.
Unlike other control algorithms that tend to linearize nonlinear systems, backstepping works without cancelling the nonlinearities in the system. This leads to more flexible designs of the control model. The backstepping control is implemented in this thesis for better performance of the quadrotor UAV for the two scenarios as well. Both control algorithms are implemented on the parameters of an unmanned quadrotor helicopter platform known as Qball-X4 available at the Networked Autonomous Vehicles Lab (NAVL) of Concordia University.
Using MATLAB/Simulink to build the simulation control model, the flight simulation of the Qball-X4 is carried out for the trajectory tracking and the payload dropping. In order to further investigate these two control approaches, the Qball-X4 is used for experimental verification on payload dropping performance. The results indicate that both algorithms can obtain acceptable performance, but the backstepping controller proves to be a better performed one.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering
Item Type:Thesis (Masters)
Authors:Qiao, Jing
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical Engineering
Date:June 2018
Thesis Supervisor(s):Zhang, Youmin
Keywords:Quadrotor UAV, Trajectory tracking,Payload dropping, Gain-Scheduled (GS) PID, Backstepping control
ID Code:984022
Deposited By: JING QIAO
Deposited On:16 Nov 2018 16:28
Last Modified:16 Nov 2018 16:28

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