IEEE Trans Cybern. 2022 Sep;52(9):9036-9047. doi: 10.1109/TCYB.2020.3045786. Epub 2022 Aug 18.
The bionic flapping-wing robotic aircraft is inspired by the flight of birds or insects. This article focuses on the flexible wings of the aircraft, which has great advantages, such as being lightweight, having high flexibility, and offering low energy consumption. However, flexible wings might generate the unexpected deformation and vibration during the flying process. The vibration will degrade the flight performance, even shorten the lifespan of the aircraft. Therefore, designing an effective control method for suppressing vibrations of the flexible wings is significant in practice. The main purpose of this article is to develop an adaptive fault-tolerant control scheme for the flexible wings of the aircraft. Dynamic modeling, control design, and stability verification for the aircraft system are conducted. First, the dynamic model of the flexible flapping-wing aircraft is established by an improved rigid finite element (IRFE) method. Second, a novel adaptive fault-tolerant controller based on the fuzzy neural network (FNN) and nonsingular fast terminal sliding-mode (NFTSM) control scheme are proposed for tracking control and vibration suppression of the flexible wings, while successfully addressing the issues of system uncertainties and actuator failures. Third, the stability of the closed-loop system is analyzed through Lyapunov's direct method. Finally, co-simulations through MapleSim and MATLAB/Simulink are carried out to verify the performance of the proposed controller.
仿生扑翼飞行器灵感来源于鸟类或昆虫的飞行。本文主要研究飞行器的柔性机翼，其具有重量轻、灵活性高和能耗低等优点。然而，柔性机翼在飞行过程中可能会产生意想不到的变形和振动。这种振动会降低飞行性能，甚至缩短飞行器的使用寿命。因此，设计一种有效的抑制柔性机翼振动的控制方法在实际中具有重要意义。本文的主要目的是为飞行器的柔性机翼开发一种自适应容错控制方案。对飞机系统进行了动力学建模、控制设计和稳定性验证。首先，采用改进的刚体有限元（IRFE）方法建立了柔性扑翼飞行器的动力学模型。其次，提出了一种基于模糊神经网络（FNN）和非奇异快速终端滑模（NFTSM）控制方案的新型自适应容错控制器，用于跟踪控制和柔性机翼的振动抑制，同时成功解决了系统不确定性和执行器故障的问题。第三，通过李雅普诺夫直接法分析了闭环系统的稳定性。最后，通过 MapleSim 和 MATLAB/Simulink 进行了联合仿真，验证了所提出控制器的性能。
