Performance Evaluation of Linear Quadratic Regulator and Linear Quadratic Gaussian Controllers on Quadrotor Platform
M Islam1, M Okasha2, E Sulaeman3, S Fatai4, A Legowo5
1M Islam, Department of Mechanical Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia.
2M Okasha, Aviation Engineering Division, Higher Colleges of Technology, UAE.
3E Sulaeman, Department of Mechanical Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia.
4S Fatai, Department of Mechanical Engineering, University of Malaya, Kuala Lumpur, Malaysia.
5A Legowo, Aviation Engineering Division, Higher Colleges of Technology, UAE.
Manuscript received on 22 March 2019 | Revised Manuscript received on 03 April 2019 | Manuscript Published on 18 April 2019 | PP: 191-195 | Volume-7 Issue-6S March 2019 | Retrieval Number: F02380376S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The purpose of this article is to evaluate the performances of the three different controllers such as Linear Quadratic Regulator (LQR), 1-DOF (Degree of Freedom) Linear Quadratic Gaussian (LQG) and 2-DOF LQG based on Quadrotor trajectory tracking and control effort. The basic algorithm of these three controllers are almost same but arrangement of some additional features, such as integral part and Kalman filter in the 1-DOF and 2-DOF LQG, make these two LQG controllers more robust comparing to LQR. Circular and Helical trajectories have been adopted in order to investigate the performances of the controllers in MATLAB/Simulink environment. Remarkably the 2-DOF LQG ensures its highly robust performance when system was considered under uncertainties. In order to investigate the tracking performance of the controllers, Root Mean Square Error (RMSE) method is adopted. The 2-DOF LQG significantly ensures that the error is less than 5% RMSE and maintains stable control input continuously.
Keywords: LQR; LQG; Quadrotor; Trajectory Tracking; Noise and Disturbance Rejection; Controller Robustness.
Scope of the Article: Quality Control