基于输出反馈控制策略的合成射流致动器LCO抑制新方法

Natalie Ramos Pedroza, W. MacKunis, V. Golubev
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引用次数: 3

摘要

本文提出了一种滑模控制方法,并证明了该方法可以有效地抑制无人机机翼的渐近极限环振荡。针对机载计算资源有限的小型无人机(SUAV)的应用,所提出的控制律被设计为实现成本低廉,不需要自适应律、函数逼近器或俯仰和俯冲速度测量。控制设计中的挑战包括由于SJA动态模型中固有的参数不确定性和非线性而导致的输入乘法不确定性。为了达到这一目的,将滑模控制策略与速度估计器相结合,并利用一组动态滤波器设计速度估计器。这是第一个在不确定的非线性SJA动态模型存在的情况下实现渐近LCO调节的输出反馈控制结果,而不使用自适应律或神经网络。利用详细的SUAV动力学模型和严格的lyapunov稳定性分析来证明俯仰和俯冲位移的渐近调节,并提供数值仿真结果来验证所提出的控制设计的性能。
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A new method of synthetic jet actuator-based LCO suppression using an output feedback control strategy
A sliding mode control method is presented in this paper, which is proven to achieve asymptotic limit cycle oscillation (LCO) suppression in unmanned aerial vehicle wings equipped with synthetic jet actuators (SJA). With a focus on applications involving small unmanned aerial vehicles (SUAV) with limited onboard computing resources, the proposed control law is designed to be inexpensively implemented, requiring no adaptive laws, function approximators, or pitching and plunging velocity measurements. Challenges in the control design include input-multiplicative uncertainty due to the parametric uncertainty and nonlinearity that are inherent in the SJA dynamic model. To achieve the result, a sliding mode control strategy is amalgamated with a velocity estimator, which is designed using a bank of dynamic filters. This is the first output feedback control result that achieves asymptotic LCO regulation in the presence of an uncertain, nonlinear SJA dynamic model, without the use of adaptive laws or neural networks. A detailed model of the SUAV dynamics is utilized along with a rigorous Lyapunov-based stability analysis to prove asymptotic regulation of the pitching and plunging displacements, and numerical simulation results are provided to demonstrate the performance of the proposed control design.
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