Open Access Article

Title: Control of a quadrotor group based on maximum hands-off distributed control

Authors: Kimiko Motonaka; Takuya Watanabe; Yuhwan Kwon; Masaaki Nagahara; Seiji Miyoshi

Addresses: Department of Electrical Electronic and Information Engineering, Kansai University, Osaka, Japan ' Department of Electrical Electronic and Information Engineering, Kansai University, Osaka, Japan ' Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan ' Institute of Environmental Science and Technology, The University of Kitakyushu, Fukuoka, Japan ' Department of Electrical Electronic and Information Engineering, Kansai University, Osaka, Japan

Abstract: This paper presents the implementation of maximum hands-off distributed control in a quadrotor group. We assume that individual quadrotors can only communicate with neighbouring quadrotors to obtain state information and do not know the state of the whole group. The maximum hands-off distributed control is an extension of the consensus control using sparse optimal control. It converges the state of a group using only local information while maximising the time when the control input is zero by optimising the consensus control input through sparse optimisation. This minimises the time required for control and reduces energy consumption. We applied this control to a four-quadrotor group using MATLAB and CoppeliaSim simulations. The results confirm that the four quadrotors converged to the same state and the control inputs became sparse. Experiments using four small Tello EDU quadrotors further confirmed that they could reach the same altitude using the maximum hands-off distributed controller.

Keywords: multi-agent system; consensus control; sparse optimal control; maximum hands-off distributed control; unmanned aerial vehicle; distributed control.

DOI: 10.1504/IJMA.2021.120377

International Journal of Mechatronics and Automation, 2021 Vol.8 No.4, pp.200 - 207

Received: 17 Sep 2021
Accepted: 05 Oct 2021

Published online: 17 Jan 2022 *