Fixed-Time Neural Control of a Quadrotor UAV With Input and Attitude Constraints

• Published in: IEEE/CAA journal of automatica sinica Vol. 10; no. 1; pp. 281 - 283
• Main Authors: Gao, Benke, Liu, Yan-Jun, Liu, Lei
• Format: Journal Article
• Language: English
• Published: Piscataway Chinese Association of Automation (CAA) 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); School of Electrical Engineering,Liaoning University of Technology,Jinzhou 121001,China%College of Science,Liaoning University of Technology,Jinzhou 121001,China
• Subjects: Attitude control; Constraint modelling; Neural networks; Unmanned aerial vehicles; Unmanned helicopters
• ISSN: 2329-9266; 2329-9274
• DOI: 10.1109/JAS.2023.123045

This letter is concerned with the attitude control of a quadrotor unmanned aerial vehicle (UAV) subject to the input constraint, attitude constraint and model uncertainty. Firstly, we construct an auxiliary system to eliminate the adverse impact of the input saturation. Secondly, we introduce the nonlinear state-dependent function to deal with the attitude constraint directly. Thirdly, the neural network is utilized to identify the unknown terms in the system. Finally, with the help of the backstepping technology, a fixed-time control scheme is presented, which guarantees that the desired signal is followed with the fixed-time convergent rate. The effectiveness of the proposed scheme is validated by a simulation verification.