Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume 34, Issue 12, Pages 10387-10397Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2022.3166531
Keywords
Attitude control; Autonomous aerial vehicles; Backstepping; Control systems; Explosions; Error compensation; Convergence; Disturbance observer; finite-time command filtered (FTCF) backstepping; human-in-the-loop (HiTL); radial basis function neural networks (RBF NNs); unmanned aerial vehicle (UAV) systems
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This article focuses on the event-based finite-time neural attitude consensus control problem for the six-rotor unmanned aerial vehicle (UAV) systems with unknown disturbances. It addresses the issues of external disturbances and uncertain nonlinear dynamics using a disturbance observer and radial basis function neural networks (RBF NNs). The proposed finite-time command filtered (FTCF) backstepping method effectively manages the complexity explosion problem and an event-triggered mechanism is considered to alleviate the communication burden.
This article focuses on the event-based finite-time neural attitude consensus control problem for the six-rotor unmanned aerial vehicle (UAV) systems with unknown disturbances. It is assumed that the six-rotor UAV systems are controlled by a human operator sending command signals to the leader. A disturbance observer and radial basis function neural networks (RBF NNs) are applied to address the problems regarding external disturbances and uncertain nonlinear dynamics, respectively. In addition, the proposed finite-time command filtered (FTCF) backstepping method effectively manages the issue of ``explosion of complexity,'' where filtering errors are eliminated by the error compensation mechanism. In addition, an event-triggered mechanism is considered to alleviate the communication burden between the controller and the actuator in practice. It is shown that all signals of the six-rotor UAV systems are bounded and the consensus errors converge to a small neighborhood of the origin in finite time. Finally, the simulation results demonstrate the effectiveness of the proposed control scheme.
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