Composite Learning Attitude Consensus for Multi-Quadrotor Systems with Parametric Uncertainties

• Published in: Proceedings of ... IEEE International Conference on Unmanned Systems (Online) pp. 518 - 523
• Main Authors: Zhou, Yan, Wen, Guanghui, Nie, Jing, Nan, Xiaoya
• Format: Conference Proceeding
• Language: English
• Published: IEEE 13.10.2023
• Subjects: Adaptive systems; attitude consensus; Attitude control; Backstepping; backstepping control; composite learning; Estimation error; Multi-quadrotor system; Parameter estimation; parametric uncertainty; Protocols; Uncertainty
• ISSN: 2771-7372
• DOI: 10.1109/ICUS58632.2023.10318397

This article investigates the attitude consensus of multi-quadrotor systems subject to parametric uncertainties. Some special auxiliary variables are given to construct the tracking errors. By integrating composite learning into backstepping control, a team of distributed adaptive controllers are established. In composite learning, tracking errors and prediction errors are used for designing parameter adaptive laws, where prediction errors are generated by the integrals of auxiliary variables over moving time intervals. It is shown that under some interval exci-tation conditions that are much weaker than persistent excitation conditions, the exponential convergence of parameter estimation errors and tracking errors can be realized, as well as the attitude consensus. Finally, the validity of the presented control scheme is demonstrated by performing numerical simulations.