Modeling of fixed wing UAV and design of multivariable flight controller using PID tuned by local optimal control | ||||
| International Conference on Aerospace Sciences and Aviation Technology | ||||
| Article 18, Volume 18, Issue 18, April 2019, Page 1-19 PDF (2.91 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.1088/1757-899X/610/1/012016 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Eslam Nabil Mobarez1; Amr Sarhan2; Mahmoud Mohamed Ashry1 | ||||
| 1Department of Optoelectronics and Control, Military Technical College, Cairo, Egypt. | ||||
| 2Aircraft electrical equipment, Military Technical College, Cairo, Egypt. | ||||
| Abstract | ||||
| Ultrastick-25e is an unmanned air vehicle fabricated by University of Minnesota. The traditional PI control was purposed for Ultrastick-25e in both longitudinal and lateral branches. Throughout this paper, PI and PID controllers are purposed for Ultrastick-25e in both longitudinal and lateral branches of linear and nonlinear model. Two tuning methods are utilized to enhance the autopilot response of Ultrastic-25e UAV. The autopilot system robustness is tested by measuring the capability of the controllers in rejecting the wind disturbances, and attenuating the noises generated from the sensors. The genetic algorithm optimizer is utilized as the first method for tuning the PI and PID controllers and enhance the performance and robustness of the system. The Local Optimal Control (LOC) is utilized as the second method for tuning the PI and PID after that. The essential contribution of this paper is utilizing local optimal control for tuning parameters of PI and PID on UAVs for the first time. The comparative study of the results assure the superiority of this tuning method over the other tuning methods used. | ||||
| Keywords | ||||
| Equations of motion; Mathematical modeling; linearization; Genetic algorithm; Local optimal control; PID tuning techniques | ||||
|
Statistics Article View: 97 PDF Download: 336 |
||||
