A neural network approach to a cooperative balancing problem in quadrotor-unmanned aerial vehicles (QUAVs)

• Main Authors: Faelden, Gerard Ely U., Maningo, Jose Martin Z., Nakano, Reiichiro Christian S., Bandala, Argel A., Dadios, Elmer P.
• Format: text
• Published: Animo Repository 2016
• Subjects: Drone aircraft—Control systems; Neural networks (Computer science); Electrical and Computer Engineering; Electrical and Electronics; Systems and Communications
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1905
• Institution: De La Salle University

There is growing interest in unmanned aerial vehicles (UAVs) such as quadrotors over the past several years. Cooperation among multiple quadrotors is one of the areas of focus. This paper proposes a neural network form of control for a cooperative task done by four quadrotors and will be tested through simulations. The task at hand is a ball and plate balancing problem during flight of multiple quadrotors carrying the plate. The objective is to maintain the keep the ball at the center of the plate even if the ball is introduced at different parts of the plate. The neural network controller will output the appropriate motor speeds of the rotors based on the detected area of introduction of the ball. Results show that the artificial neural network controller successfully directs the ball towards the center of the plate. The network outputs an average deviation of 0.00924 units from the expected PWM signal strength which corresponds to a 0.249% error from the expected value. © 2015 IEEE.