Autonomous Quadcopter Control System Design Using LQG Controller to Perform Obstacle Avoidance

Abstract

This research presents the implementation of the Linear Quadratic Gaussian (LQG) Controller and LiDAR sensors on the quadcopter used to avoid obstacles. The LQG controller is a combination of a Linear Quadratic Regulator (LQR) with a Kalman Filter as a State Estimator. The results of the estimate by Kalman Filter are compared against the actual value of the measurement by reviewing the Mean Square Error value. Linear position and angular position are variables that are controlled in the LQG control system to perform obstacle avoidance. The variations used in this study are the Q and R matrix values in the LQG controller design. Some of the tests that have been carried out include the open loop test, the closed loop test, the quadcopter test without an obstacle and the quadcopter test with an obstacle. The test results show that the quadcopter is able to follow the flight reference path and that the obstacle avoidance algorithm designed produces a quadcopter that is able to avoid obstacles. The test results show that the Q and R matrices on the Gain Regulator and Kalman filters can affect the quadcopter in carrying out avoidance.