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...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IOP Publishing
2017
|
| Subjects: | |
| Online Access: | 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 http://irep.iium.edu.my/62846/ http://iopscience.iop.org/article/10.1088/1757-899X/270/1/012009/pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| 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 |
|---|