Gain scheduled linear quadratic control for quadcopter

This study exploits the dynamics and control of quadcopters using Linear Quadratic Regulator (LQR) control approach. The quadcopter’s mathematical model is derived using the Newton-Euler method. It is a highly manoeuvrable, nonlinear, coupled with six degrees of freedom (DOF) model, which include...

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Bibliographic Details
Main Authors: Okasha, Mohamed Elsayed Aly Abd Elaziz, Shah, J., Fauzi, W, Hanouf, Zahir
Format: Conference or Workshop Item
Language:English
English
Published: IOP Publishing 2017
Subjects:
Online Access:http://irep.iium.edu.my/62846/
http://irep.iium.edu.my/62846/
http://irep.iium.edu.my/62846/
http://irep.iium.edu.my/62846/1/62846%20Gain%20scheduled%20linear%20quadratic.pdf
http://irep.iium.edu.my/62846/2/62846%20Gain%20scheduled%20linear%20quadratic%20SCOPUS.pdf
Description
Summary:This study exploits the dynamics and control of quadcopters using Linear Quadratic Regulator (LQR) control approach. The quadcopter’s mathematical model is derived using the Newton-Euler method. It is a highly manoeuvrable, nonlinear, coupled with six degrees of freedom (DOF) model, which includes aerodynamics and detailed gyroscopic moments that are often ignored in many literatures. The linearized model is obtained and characterized by the heading angle (i.e. yaw angle) of the quadcopter. The adopted control approach utilizes LQR method to track several reference trajectories including circle and helix curves with significant variation in the yaw angle. The controller is modified to overcome difficulties related to the continuous changes in the operating points and eliminate chattering and discontinuity that is observed in the control input signal. Numerical non-linear simulations are performed using MATLAB and Simulink to illustrate to accuracy and effectiveness of the proposed controller